Systems and methods for proactive listening bot-plus person advice chaining

ABSTRACT

A pervasive user experience capable of integrating robo-advising with human advising is discussed. Conversations and other inputs may be actively captured to identify issues with which the system may be able to assist. Inputs from multiple conversations separated in time may be correlated to identify relevant needs and goals. Recommendations and strategies may be developed and presented to the customer. When it is determined that human advising is appropriate for one or more issues, the customer may be connected to an advisor for assistance with particular issues. Transitions may be facilitated to allow customers to more efficiently return to robo-advising until human advising is again deemed appropriate.

CROSS REFERENCE TO RELATED APPLICATION

This application claims priority to U.S. Provisional Patent ApplicationNo. 62/666,587 entitled “SYSTEMS AND METHODS FOR PROACTIVE LISTENINGBOT-PLUS PERSON ADVICE CHAINING,” filed May 3, 2018, and to U.S. PatentApplication No. 62/666,591 entitled “SYSTEMS AND METHODS FOR PERVASIVEADVISOR FOR MAJOR EXPENDITURES,” filed May 3, 2018, both incorporatedherein by reference in their entireties.

BACKGROUND

People are often unintentional about how they spend money. Withoutnecessarily realizing it, many people tend to spend more than they canafford. The financial health of a person is correlated to the financialdecisions that person makes, but a significant number of people tend notto be aware of what affirmative steps they can take to improve theirfinancial situation. Often times people have difficulty keeping track oftheir finances and managing their credit. Beyond being more informedabout their account balances, users often lack information on actionsthey could take and how those actions would impact their financialsituation. Sometimes, people may mistakenly believe that they lacksufficient financial assets to have additional options or to warrantseeking financial advice. And many may feel they do not have the time orenergy to devote to figuring it their options.

Moreover, as a result of certain life events, or in anticipation of anevent that may warrant an adjustment to personal finances, a person maydesire to get their finances under control in order to meet a financialgoal. However, even though a person may realize that a life event couldhave substantial effects on their finances, the person often is notsufficiently well-informed to know where to begin. A person maygenerally appreciate there are opportunities and pitfalls, but may befrozen into inaction over uncertainty about when it is time to seekadvice.

Further, people normally appreciate that, with the right help, theycould enhance their financial situation. But finding the help that isneeded is often a challenge. Sometimes people lack knowledge about theroles and abilities of types of professionals, and do not know whichones (or how) to contact for professional help. Often, a person whowants the aid of a financial professional blindly initiates contact bygoing into a physical location, like a bank, or calling a professionalover the phone without knowing whether the professional is well-suitedto help based on the person's particular financial and lifecircumstances. In the alternative, the person sometimes relies onnon-professional suggestions or does not obtain the advice needed atall. And even if a professional with the right background is found,arranging a meeting or discussion can be another challenge. The processof comparing schedules and finding a time that is convenient forcustomer and that fits with the professional's schedule can be daunting,especially if last-minute meetings and commitments require flexibilityin scheduling.

And when a customer finally is able to connect with a professional, theinteractions are often inefficient and unnecessarily time-consumingbecause the customer must spend a significant amount of time bringingthe professional “up to speed” by explaining his or her lifecircumstances, financial situation, motivations for seeking help,overall needs and concerns, etc. Sometimes, after the professional isbrought up to speed, it becomes apparent that the customer's needs aremore well-suited for a different professional for various reasons, andthe customer may be back at “square one,” having to find anotherprofessional, arrange for another meeting or discussion, and once againexplain his or her situation to bring the new professional up to speed.The process can sometimes feel insurmountable with seemingly countlessoptions for financial products and professionals, and countlessvariables affecting the choices that can or should be made. And withother time commitments in life, many customers may put off seeking help,perhaps indefinitely, and thus do not benefit from needed services thatcould help them achieve their goals.

Furthermore, sometimes a financial professional's assistance is neededfor a short time, for a small part of the advising process, orintermittently as needs arise. But it can be very time consuming andinefficient to reach out to professionals for “small chunks” ofassistance because the customer must take time to explain changes in hisor her situation to fill in the gaps for the professional each timethere is an interruption in service. And in the interim, the customer isoften without adequate tools that could help the customer stay on trackbased on the advice of the professional, and to seamlessly return to theprofessional for advice only when needed. On the flip side, an advisorserving a customer may provide the assistance that required his or herparticular expertise, but the customer may also take the advisor's timefor issues that could then be handled just as well without the advisor'shelp, making the process less efficient for the advisor.

Current technologies are not able to meet the needs of customers andadvisors. Smart speakers, for example, may listen for a request forinformation (such as the weather or the contents of an incoming textmessage), but such user devices are not capable of understanding auser's needs and providing recommendations based on the user'scircumstances. And even if such devices were capable of providing usefulrecommendations to users, even as the user's circumstances change, thedevices do not identify situations in which the device's capabilitiesare inadequate in some way based on the particular needs of a customer,and provide a mechanism for efficiently transitioning to a humanadvisor. And moreover, user devices do not take the informationdiscussed with others or assistance received from human advisors intoaccount in making future recommendations. The user's goals andstrategies may have changed based on the assistance of the humanadvisor, and any recommendations from the user device would noteffectively reflect such changes.

What are needed are systems and methods that address one or more of theabove, as well as other, shortcomings of conventional approaches.

SUMMARY

Example systems and methods relate to providing a pervasive userexperience capable of integrating robo-advising with human advising.Conversations and other inputs may be actively captured to identifyissues with which the system may be able to assist. Inputs from multipleconversations separated in time may be correlated to identify relevantneeds and goals. Recommendations and strategies may be developed andpresented to the customer. When it is determined that human advising isappropriate for one or more issues, the customer may be connected to anadvisor for assistance with particular issues. Transitions may befacilitated to allow customers to more efficiently return torobo-advising until human advising is again deemed appropriate.

Various embodiments of the disclosure relate to a service providercomputing system. The service provider computing system may comprise adatabase with a user profile corresponding to a user. The serviceprovider computing system may also comprise a network interfaceconfigured to communicatively couple the service provider computingsystem to computing devices. The network interface may be configured tocommunicatively couple the service provider computing system to a firstcomputing device. The first computing device may have a sound sensor fordetecting ambient sounds. The first computing device may also have afirst set of one or more user interfaces. The first set of userinterfaces may be for perceptibly presenting information to the userand/or for receiving user inputs. The network interface may also beconfigured to communicatively couple the service provider computingsystem to a second computing device. The second computing device mayhave a second set of one or more user interfaces. The second set of userinterfaces may be for perceptibly presenting information to an advisorand/or for receiving advisor inputs. At least one of the first computingdevice and the service provider computing system may be configured todetect a goal. The first computing device and/or the service providercomputing system may be configured to detect the goal by capturingambient sounds using the sound sensor of the first computing device. Thefirst computing device and/or the service provider computing system mayalso be configured to detect the goal by extracting a set of one or morevoice inputs. The set of voice inputs may be of the user. The set ofvoice inputs may be extracted from a subset of the ambient soundscaptured using the sound sensor. The first computing device and/or theservice provider computing system may moreover be configured to detectthe goal by identifying the goal based at least on an analysis of theset of voice inputs. The first computing device and/or the serviceprovider computing system may also be configured to initiate a livecommunication session. The live communication session may be initiatedbetween the first and second computing devices. The first computingdevice and/or the service provider computing system may moreover beconfigured to present a virtual dashboard via the first and second setsof user interfaces during the live communication session. The virtualdashboard may be configured to perceptibly present an identification ofthe goal. The identification of the goal may be perceptibly presentedvia the second set of user interfaces.

In one or more implementations, at least one of the first computingdevice and the service provider computing system may be configured toidentify select data from the user profile relevant to the goal. Thevirtual dashboard may be configured to perceptibly present the selectdata.

In one or more implementations, the sound sensor of the first computingdevice may be configured to pervasively capture ambient sounds to detectgoals.

In one or more implementations, at least one of the first computingdevice and the service provider computing system may be configured todetect an urgency of the goal. The urgency of the goal may be detectedbased on at least one of speed, tone, or aggression of user speech.

In one or more implementations, the virtual dashboard may be configuredto perceptibly present a graphic depiction of the user's progresstowards achieving the goal.

In one or more implementations, the virtual dashboard may be configuredto present at least one of an advisor image, an advisor video, and anadvisor audio.

In one or more implementations, the virtual dashboard may be configuredto present inputs received via the second set of user interfaces. Theinputs may be presented via the first set of user interfaces. The inputsmay be received following presentation of the identification of thegoal.

In one or more implementations, the set of voice inputs may beidentified based at least in part on a biometric voice signature of theuser.

In one or more implementations, the ambient sounds include voice inputsof a second user. The voice inputs of the second user may be excludedfrom the set of voice inputs. The voice inputs of the second user may beexcluded based on a mismatch with the biometric voice signature of theuser.

In one or more implementations, the virtual dashboard may be configuredto present information exchanged during a prior live communicationsession. The information may be presented via the second set of userinterfaces.

In one or more implementations, at least one of the first computingdevice and the service provider computing system may be configured toinitiate a first robo-advising session. The first robo-advising sessionmay be initiated before initiating the live communication session. Thevirtual dashboard may be configured to present an activatable link. Theactivatable link may be activatable via the first and/or second set ofuser interfaces. When activated, the activatable link may terminate thelive communication session. Additionally or alternatively, whenactivated, the activatable link may initiate a second robo-advisingsession.

In one or more implementations, the sound sensor is a first soundsensor. The second computing device may comprise a second sound sensor.At least one of the first computing device, the second computing device,and the service provider computing device may be configured to detectthe goal. The goal may be detected based on a combination of multiplefragmented issue indicators. The fragmented issue indicators may beidentified in multiple voice inputs. The voice inputs may be capturedusing the first and second sound sensors of the first and secondcomputing devices.

In one or more implementations, the set of voice inputs may be a firstset of voice inputs. The user may be a first user. At least one of thefirst computing device and the service provider computing system may beconfigured to extract a second set of one or more voice inputs. Thesecond set of voice inputs may be of a second user. The second set ofvoice inputs may be extracted from the subset of the ambient soundscaptured using the sound sensor. At least one of the first computingdevice and the service provider computing system may also be configuredto identify the goal based at least on an analysis of both the first andsecond sets of voice inputs.

In one or more implementations, the first and second sets of voiceinputs may be separated by multiple days.

In one or more implementations, at least one of the first computingdevice and the service provider computing system may be configured todetect a robo-advising transition trigger. The robo-advising transitiontrigger may be detected during the live communication session. At leastone of the first computing device and the service provider computingsystem may also be configured to terminate the live communicationsession. At least one of the first computing device and the serviceprovider computing system may moreover be configured to initiate arobo-advising session.

In one or more implementations, the live communication session is afirst live communication session. At least one of the first computingdevice and the service provider computing system may be configured todetect a human-advising transition trigger. At least one of the firstcomputing device and the service provider computing system may beconfigured to detect the human-advising transition trigger during therobo-advising session. At least one of the first computing device andthe service provider computing system may also be configured to initiatea second live communication session between the first and secondcomputing devices. The second live communication session may beinitiated in response to detection of the human-advising transitiontrigger. At least one of the first computing device and the serviceprovider computing system may moreover be configured to provide thevirtual dashboard to the first and second computing devices during thesecond live communication session. The virtual dashboard being may beconfigured to perceptibly present information exchanged between thefirst and second devices during the first live communication sessionand/or during the robo-advising session.

In one or more implementations, at least one of the first computingdevice and the service provider computing system may be configured topresent information from the first live communication session and/or therobo-advising session. The information may be presented via the secondset of user interfaces.

Various embodiments of the disclosure relate to a computing device. Thecomputing device may comprise a sound sensor for detecting ambientsounds. The computing device may also comprise a first set of one ormore user interfaces for perceptibly presenting information to a userand/or for receiving user inputs. The computing device may moreovercomprise a network interface configured to communicatively couple thecomputing device to a second computing device. The second computingdevice may have a second set of one or more user interfaces forperceptibly presenting information to an advisor and/or for receivingadvisor inputs. The computing device may additionally comprise aprocessor and memory having instructions that, when executed by theprocessor, cause the processor to perform specific functions. Thecomputing device may be configured to detect a sound sample using thesound sensor. The computing device may also be configured to extract aset of one or more voice inputs of the user from the sound sample. Thecomputing device may moreover be configured to identify a goal. The goalmay be identified based at least on an analysis of the set of voiceinputs. The computing device may additionally be configured to initiatea live communication session. The live communication session may beinitiated with the second computing device. The computing device mayfurther be configured to present a virtual dashboard during the livesession. The virtual dashboard may be presented via the first set ofuser interfaces. The virtual dashboard may be configured to perceptiblypresent an identification of the goal. The identification of the goalmay be presented via the second set of user interfaces.

In one or more implementations, the network interface may be configuredto communicatively couple the computing device to a service providercomputing system. The service provider computing system may store a userprofile corresponding with the user. The user profile may be stored in adatabase. The virtual dashboard may be configured to present select datafrom the user profile. The select data may be presented, via the secondset of user interfaces. The select data may be determined to be relevantto the goal by at least one of the computing device, the secondcomputing device, and the service provider computing system. The virtualdashboard may also be configured to present inputs via the first set ofuser interfaces. The presented inputs may be received via the second setof user interfaces. The presented inputs may be received followingpresentation of the select data.

In one or more implementations, the virtual dashboard may be configuredto present a graphic depiction of the user's progress towards achievingthe goal.

Various embodiments of the disclosure relate to a method. The method maycomprise detecting ambient sounds. The ambient sounds may be detectedpervasively. The detected sounds may be detected using a sound sensor ofa first computing device. The method may also comprise extracting a setof one or more voice inputs of a user. The voice inputs may be extractedfrom a subset of the ambient sounds. The method may moreover compriseidentifying a goal of the user. The goal may be identified based atleast on an analysis of the set of voice inputs. The method mayadditionally comprise initiating a live communication session betweenthe first computing device and a second computing device. The method mayfurther comprise providing a virtual dashboard. The virtual dashboardmay be configured to an identification of the goal. The goal may bepresented perceptibly to the second computing device.

In one or more implementations, the method may comprise initiating arobo-advising session. The robo-advising session may be initiated beforeinitiating the live communication session. The method may also compriseperceptibly presenting information from the robo-advising session duringthe live communication session. The information may be presented in thevirtual dashboard.

In one or more implementations, the virtual dashboard may be configuredto present a graphical depiction of the user's progress towardsachieving the identified goal.

In one or more implementations, the method may comprise detecting arobo-advising transition trigger. The robo-advising trigger may bedetected during the live communication session. The method may alsocomprise terminating the live session. The live session may beterminated in response to detection of the robo-advising transitiontrigger.

In one or more implementations, detecting the robo-advising transitiontrigger during the live session may comprise receiving a signalindicating activation of a visually-perceptible link. The signal may bereceived via one of the user interfaces of the first and/or secondcomputing devices. The link may be indicating a desire to return torobo-advising.

Various embodiments of the disclosure relate to a method. The method maycomprise detecting a first sound sample. The first sound sample may bedetected using a sound sensor of a first device. The sound sensor may beconfigured to pervasively capture ambient sounds. The method may alsocomprise analyzing the first sound sample. The first sound sample may beanalyzed to detect a first voice input based at least in part on abiometric voice signature of a user. The method may moreover comprisedetecting an advising trigger. The advising trigger may be detectedbased at least in part on the first voice input. The method mayadditionally comprise initiating a robo-advising session. The method mayfurther comprise initiating a human advising session. Initiating thehuman advising session may comprise initiating a live communicationsession. The live communication session may be initiated between thefirst device and a second device of a human advisor. Initiating thehuman advising session may also comprise perceptibly presenting avirtual dashboard. The virtual dashboard may include graphical elementsconfigured to facilitate the human advising session between the firstand second devices.

In one or more implementations, the advising trigger is detection of agoal.

In one or more implementations, the method comprises detecting anurgency of the goal. The urgency of the goal may be detected based on atleast one of speed, tone, or aggression of user speech.

In one or more implementations, the virtual dashboard may be configuredto perceptibly present an identification of the goal. The identificationof the goal may be presented via one or more user interfaces of thesecond device.

In one or more implementations, the advising trigger is a spoken requestfor advising.

In one or more implementations, the advising trigger is a detection of atransaction. The transaction may be executed using the first device.

In one or more implementations, the transaction is a financialtransaction. The financial transaction may be implemented via a mobilewallet application. The mobile wallet application may be running on thefirst device.

In one or more implementations, the advising trigger is detection of aphysical location. The physical location may be detected using alocation sensor. The physical location may be a predetermined physicallocation. The location sensor may be a sensor of the first device.

In one or more implementations, the virtual dashboard may be configuredto perceptibly present an identification of the advising trigger.

In one or more implementations, the robo-advising session may comprisedetecting a goal. The goal may be detected based at least on the firstvoice input. The robo-advising session may also comprise formulating afirst action item for bringing the user closer to achieving the goal.The first action item may be formulated based at least in part on a userprofile. The user profile may correspond to the user. The robo-advisingsession may also moreover comprise presenting the first action item viaone or more user interfaces. The first action item may be presented viauser interfaces of the first device.

In one or more implementations, the robo-advising session may comprisereceiving one or more inputs. The one or more inputs may be received viathe first device.

In one or more implementations, the robo-advising session may comprisedetecting a human advising transition trigger. The human advisingtransition trigger may be detected in the one or more inputs. The humanadvising session may be initiated in response to detection of the humanadvising transition trigger.

In one or more implementations, the robo-advising session may comprisedetecting a goal. The goal may be detected based at least in part on oneor more inputs.

In one or more implementations, the robo-advising session may compriseformulating a first action item for bringing the user closer toachieving the goal. The first action item may be formulated based on theone or more inputs and/or on a user profile corresponding to the user.The robo-advising session may also comprise perceptibly presenting thefirst action item. The first action item may be presented via one ormore user interfaces of the first device.

In one or more implementations, receiving the one or more inputs via thefirst device may comprise detecting a second sound sample. The secondsound sample may detected using the sound sensor. The second soundsample may be detected following presentation of the first action item.Receiving the one or more inputs via the first device may also compriseanalyzing the second sound sample to detect a second voice input.

In one or more implementations, the robo-advising session may compriseformulating a second action item. The second action item may beformulated based on the second voice input and/or on the user profile.The robo-advising session may also comprise perceptibly presenting thesecond action item. The second action item may be presented via one ormore user interfaces of the first device.

In one or more implementations, the robo-advising session may be a firstrobo-advising session. The human advising session may further comprisedetecting a robo-advising transition trigger. The robo-advisingtransition trigger may be detected during the live communicationsession. The method may also comprise terminating the human advisingsession. The method may moreover comprise initiating a secondrobo-advising session. The second robo-advising session may be initiatedin response to detection of the robo-advising trigger.

Various embodiments of the disclosure relate to a service providercomputing system. The service provider computing system may comprise adatabase with a user profile corresponding to a user. The serviceprovider computing system may also comprise a network interfaceconfigured to communicatively couple the service provider computingsystem to a first device. The first device may have a sound sensor fordetecting ambient sounds. The first device may also have a first set ofone or more user interfaces for perceptibly presenting information tothe user and/or for receiving user inputs. The network interface mayalso be configured to communicatively couple the service providercomputing system to a second device. The second device may have a secondset of one or more user interfaces for perceptibly presentinginformation to an advisor and/or for receiving advisor inputs. At leastone of the first device and the service provider computing system may beconfigured to detect a first sound sample. The first sound sample may bedetected using the sound sensor of the first device. The sound sensormay be configured to pervasively capture ambient sounds. At least one ofthe first device and the service provider computing system may also beconfigured to analyze the first sound sample. The first sound sample maybe analyzed to detect a first voice input. The first voice input may bedetected based at least in part on a biometric voice signature of auser. At least one of the first device and the service providercomputing system may moreover be configured to detect an advisingtrigger. The advising trigger may be detected based at least in part onthe first voice input. At least one of the first device and the serviceprovider computing system may additionally be configured to initiate arobo-advising session. At least one of the first device and the serviceprovider computing system may further be configured to initiate a humanadvising session. The human advising session may comprise initiating alive communication session. The live communication session may beinitiated between the first device and the second device. The humanadvising session may also comprise perceptibly presenting a virtualdashboard. The virtual dashboard may comprise graphical elementsconfigured to facilitate the human advising session between the firstand second devices. The virtual dashboard may be configured toperceptibly present a subset of the user profile.

In one or more implementations, the advising trigger may be detection ofa goal. The virtual dashboard may be configured to perceptibly presentthe goal and/or a graphic depiction of the user's progress towardsachieving the goal.

In one or more implementations, the robo-advising session may comprisedetecting a goal. The goal may be detected based at least on the firstvoice input. The robo-advising session may also comprise formulating afirst action item for bringing the user closer to achieving the goal.The first action item may be formulated based at least in part on a userprofile corresponding to the user. The robo-advising session maymoreover comprise presenting the first action item via one or more userinterfaces of the first device.

Various embodiments of the disclosure relate to a computing device. Thecomputing device may comprise a sound sensor for detecting ambientsounds. The computing device may also comprise a first set of one ormore user interfaces for perceptibly presenting information to a userand/or for receiving user inputs. The computing device may moreovercomprise a network interface configured to communicatively couple thecomputing device to a second computing device. The second device mayhave a second set of one or more user interfaces for perceptiblypresenting information to an advisor and/or for receiving advisorinputs. The computing device may additionally comprise a processor andmemory having instructions that, when executed by the processor, causethe processor to perform specific functions. The computing device may beconfigured to detect a first sound sample using the sound sensor. Thesound sensor may be configured to pervasively capture ambient sounds.The computing device may also be configured to analyze the first soundsample to detect a first voice input. The first voice input may bedetected based at least in part on a biometric voice signature of auser. The computing device may moreover be configured to detect anadvising trigger. The advising trigger may be detected based at least inpart on the first voice input. The computing device may additionally beconfigured to initiate a robo-advising session. The computing device mayfurther be configured to initiate a human advising session. The humanadvising session may comprise initiating a live communication session.The live communication session may be initiated between the first deviceand the second device. The human advising session may also compriseperceptibly presenting a virtual dashboard. The virtual dashboard maycomprise graphical elements configured to facilitate the human advisingsession between the first and second devices.

In one or more implementations, the robo-advising session may comprisedetecting a goal. The goal may be detected based at least on the firstvoice input. The robo-advising session may also comprise presenting thefirst action item via the first set of user interfaces.

In one or more implementations, the instructions may cause the processorto detect a robo-advising transition trigger during the livecommunication session. The instructions may also cause the processor toterminate the live communication session. The live communication sessionmay be terminated in response to detection of the robo-advisingtransition trigger.

These and other features, together with the organization and manner ofoperation thereof, will become apparent from the following detaileddescription when taken in conjunction with the accompanying drawings.

BRIEF DESCRIPTION OF THE FIGURES

FIG. 1 is a block diagram of an example computing system framework forpervasive advising according to example embodiments.

FIG. 2 is a block diagram for example components that could beincorporated in the computing devices of the computing system frameworkof FIG. 1 according to example embodiments.

FIG. 3 depicts an implementation of an example pervasive advising systemwith a virtual dashboard according to example embodiments.

FIG. 4 depicts an example method of advising a user according to exampleembodiments.

FIG. 5 depicts an example method for transitioning between robo-advisingand human advising according to example embodiments.

FIG. 6 depicts an example profile applicable to advising of one or moreusers according to example embodiments.

FIG. 7 depicts an example method of advising users according to exampleembodiments.

FIG. 8 depicts an example graphical user interface of a potentialvirtual dashboard according to example embodiments.

FIG. 9 depicts an example communication between a consumer device and aprovider computing device according to example embodiments.

FIG. 10 depicts an example graphical user interface of a potentialvirtual dashboard according to example embodiments.

FIG. 11 depicts an example graphical user interface of a potentialvirtual dashboard according to example embodiments.

FIG. 12 depicts an example graphical user interface of a potentialvirtual dashboard according to example embodiments.

FIG. 13 depicts an example graphical user interface of a potentialvirtual dashboard accessible according to example embodiments.

FIG. 14 depicts example notifications for pervasive advising accordingto example embodiments.

FIG. 15A depicts an example graphical user interface for a possibleinteraction between a customer and advisor according to exampleembodiments.

FIG. 15B depicts an example graphical user interface for a possibleinteraction between a customer and advisor according to exampleembodiments.

FIG. 15C depicts an example graphical user interface for a possibleinteraction between a customer and advisor according to exampleembodiments.

FIG. 16 depicts an example graphical user interface for a potentialvirtual dashboard accessible customers and/or advisors according toexample embodiments.

FIG. 17 depicts an example graphical user interface for an interactionbetween a customer and advisor according to example embodiments.

DETAILED DESCRIPTION

Disclosed is an approach for providing a pervasive user experiencecapable of effectively integrating robo-advising with as-needed humanadvising. Example systems and methods may include a proactive listeningbot and/or other consumer computing devices configured to activelydetect conversations and determine that a financial issue is beingdiscussed. Based on the financial discussions, a financial strategy maybe developed. As used herein, the term “financial strategy” may be usedto refer to a strategy generated to meet a financial goal. A financialstrategy may include a financial plan, budget, investment strategy, orcombination thereof. The system may include one or more consumercomputing devices in communication with a computing system of aprovider, which may be a financial institution. A consumer computingdevice may be structured to detect a voice input, and the consumercomputing device and/or the provider computing system may determine thata financial goal (e.g., a major expenditure, credit repair, transaction,or purchase such as a vacation, new home, expensive jewelry, or anyother purchase requiring substantial funding) was or is being discussed.The consumer computing devices may communicate or otherwise present(via, e.g., an application that generates a virtual dashboard or otheruser interface) a financial strategy for meeting the financial goal inresponse to the detection of the voice input and identification of thefinancial goal. The connected computing device and/or provider computingsystem may advise a customer to connect with an advisor computing deviceof an advisor (who need not be associated with the provider) based on,for example, the customer's financial goals. The system may match thecustomer with a suitable advisor, schedule a meeting, and facilitate adiscussion via, for example, an application running on the consumercomputing device that connects the consumer computing device with theadvisor computing device. The user computing device, advisor computingdevice, and/or provider computing device may update the financial goalsand/or financial strategy (e.g., by extracting relevant informationexchanged or discussed in the meeting), and continue advising the useras before, informed by the information exchanged in the meeting, untilanother issue warranting connection with an advisor computing device isidentified and the user wishes to connect with the same (or another)advisor computing device.

Embodiments and implementations of the systems and methods disclosedherein improve current computing systems by providing proactive andpervasive user experiences involving seamless or otherwise substantiallyenhanced) transitions between robo-advising and human advising. In someimplementations, financial goals affecting multiple users may beidentified based on, for example, already-known associations ofcomputing devices of existing customers with a provider computingsystem. The system may include mechanisms (e.g., digital voiceassistants, biometric scanners, and so on) for authenticating users toenable simultaneous financial advising for multiple users. Identitiesmay be verified in various ways to prevent fraudulent activity and toensure that each person who interacts with the proactive listening botoperates under the proper security roles and permissions. A “ubiquitous”proactive listening bot (i.e., a bot that may be configured to detectsignals using multiple or all computing devices of one or more customersat all times or until turned off or otherwise deactivated) can bestructured to identify financial goals and needs that users may be ableto identify for themselves due to a lack of information or expertise.Users who may not be aware of a potential strategy for improving theirfinancial health need not manually enter a large quantity of informationthat may be irrelevant (by, e.g., answering a large number of questionsthat are intended to reveal (“fish” for) financial issues that may ormay not exist). Without such requirements, the computing resourcesneeded (e.g., processing time, programmatic instructions, memoryutilization, etc.), are reduced.

In some situations, advise from a professional may be needed. However,even after the right advisor is found, connecting with the advisor andproviding needed information is a time-consuming and inefficientprocess. For example, professional advisors tend to use their owndevices and are generally part of separate computing environments. Bymatching a user with the right advisor based on information acquiredproactively (by, e.g., listening to the user and without requiringseparate user entry), and by allowing calendar sharing and syncing, theuser is able to easily find an advisor and schedule meetings in lesstime and with reduced demand for computing resources.

Moreover, conventionally, to provide an advisor with financialinformation about him/herself (and others affected by the user'sfinancial health), the user could share his or her login credentials toallow the advisor to access the user's financial accounts to retrievethe information needed. However, this is a great security risk, islikely to share too much personal information, and can be over-inclusive(requiring the advisor to spend additional time extracting relevantinformation from a large amount of data). And after each interactionwith the advisor, the customer conventionally must manually update hisor her financial records. By interfacing with the advisor's system,security risks are reduced, as are the time and processing resourcesrequired to keep financial records updated. The facilitated transitionsbetween robo-advising and human advising disclosed herein involves anunconventional solution to a technological problem.

Further, the disclosed approach improves computing systems by using oneor more computing devices to interact with a user (e.g., a customer) viavoice recognition and analytics that pervasively and interactivelyprovide financial planning advice to users. Rather than requiring a userto dedicate time and computing resources to determining one's financialneeds and goals and researching available options (e.g., by filling outa questionnaire intended to identify issues/needs/goals and seekingsources of information from various databases), user devices can acquirethe information without requiring the user to dedicate time or otherwisechange daily activities. User computing devices are not limited tosingle, one-time statements in determining customer goals and needs, butcan obtain the needed information over the course of a day, a week, amonth, or longer, based on multiple conversations with family andfriends, consultations with advisors, and/or other activities. Thissaves a computing device from having to either remain silent because notenough is known to provide a relevant or useful recommendation, orprovide recommendations that are likely to be irrelevant or unhelpfulbecause they are based on tidbits of information or on conjecture.Systems, methods, and computer implementations disclosed herein improvethe functioning of such systems and information management by providingunconventional, inventive functionalities that are novel and non-obviousimprovements over current systems.

Referring to FIG. 1, a block diagram of a proactive advising system 100is shown according to one or more example embodiments. As describedherein, the proactive advising system 100 enables the implementation ofpervasive user experiences involving facilitated transitions betweenrobo-advising and human advising. As used herein, robo-advising, botadvising, robot advising, and like terms refer to advising that does notinvolve interaction with, or intervention by, a person. Robo-advisingmay be implemented using one or more mobile or non-mobile computingdevices capable of acquiring inputs from a user (e.g., a user'scommunications) and automatically performing actions, or providingrecommendations for future actions by the user, that affect the user'scircumstances. The robo-advising may be accomplished using, for example,artificial intelligence tools, intelligent agents, machine learning, orother logic and algorithms capable of extracting relevant informationfrom input streams that include both relevant and non-relevantinformation (e.g., conversations that may span multiple days and coverrelated and unrelated topics).

The proactive advising system 100 includes one or more providercomputing devices 110 (of one or more service providers), one or moreconsumer computing devices 120 (of one or more users receiving one ormore financial or other services from the service provider), one or moreadvisor computing devices 130 (of one or more persons who advise users,and who may or may not be associated with the service provider), and oneor more third-party computing devices 140 (of entities that are separatefrom the service provider). Each provider computing device 110, consumercomputing device 120, advisor computing device 130, and third-partycomputing device 140 may include, for example, one or more mobilecomputing devices (e.g., smartphones, tablets, laptops, smart devicessuch as home smart speakers and watches, etc.), non-mobile computingdevices (such as desktop computers, workstations, servers, etc.), or acombination thereof.

Provider computing devices 110, consumer computing devices 120, advisorcomputing devices 130, and third-party computing devices 140 may becommunicably coupled to each other over a network 150, which may be anytype of communications network. The network 150 may involvecommunications using wireless network interfaces (e.g., 802.11X, ZigBee,Bluetooth, near-field communication (NFC), etc.), wired networkinterfaces (e.g., Ethernet, USB, Thunderbolt, etc.), or any combinationthereof. Communications between devices may be direct (e.g., directlybetween two devices using wired and/or wireless communicationsprotocols, such as Bluetooth, WiFi, NFC, etc.), and/or indirect (e.g.,via another computing device using wired and/or wireless communicationsprotocols, such as via the Internet). The network 150 is structured topermit the exchange of data, values, instructions, messages, and thelike between and among the provider computing devices 110, the consumercomputing devices 120, the advisor computing devices 130, and thethird-party computing devices 140 via such connections.

Referring to FIG. 2, computing device 200 is representative of examplecomputing devices that may be used to implement proactive advisingsystem 100, such as one or more provider computing devices 110, consumercomputing devices 120, advisor computing devices 130, and/or third-partycomputing devices 140. Not every provider computing device 110, consumercomputing device 120, advisor computing device 130, and third-partycomputing device 140 necessarily requires or includes all of the exampledevice components depicted in FIG. 2 as being part of computing device200. Multiple computing devices 200 (each with a potentially differentset of components, modules, and/or functions) may be used by one serviceprovider (e.g., a financial institution providing financial and otherservices), one user (e.g., a customer receiving financial advice), oneadvisor (e.g., a professional who provides financial advice suited to acustomer's circumstances), or one third party (e.g., a credit agency,government agency, merchant, or other source of information or providerof services). Similarly, one computing device 200 may be used bymultiple service providers, multiple users, multiple advisors, ormultiple third-parties.

Each computing device 200 may include a processor 205, memory 210, andcommunications interface 215. Each processor 205 may be implemented as ageneral-purpose processor, an application specific integrated circuit(ASIC), one or more field programmable gate arrays (FPGAs), a digitalsignal processor (DSP), a group of processing components, or othersuitable electronic processing components structured to control theoperation of the computing device 200. The memory 210 (e.g., RAM, ROM,NVRAM, Flash Memory, hard disk storage) may store data and/or computercode for facilitating at least some of the various processes describedherein. In this regard, the memory 210 may store programming logic that,when executed by the processor 205, controls the operation of thecomputing system 200. Memory 210 may also serve as one or more datarepositories (which may include, e.g., database records such as user andaccount data and data acquired from various sources). The communicationsinterface 215 may be structured to allow the computing device 200 totransmit data to and receive data from other mobile and non-mobilecomputing devices (e.g., via network 150) directly or indirectly.

Each computing device 200 may include one or more other components(generally involving additional hardware, circuitry, and/or code)depending on the functionality of the computing device 200. Userinterfaces 220 include any input devices (e.g., keyboard, mouse,touchscreen, microphone for voice prompts, buttons, switches, etc.) andoutput devices (e.g., display screens, speakers for sound emission,notification LEDs, etc.) deemed suitable for operation of the computingdevice 200. Computing device 200 may also include one or more biometricscanners 225, such as fingerprint scanners, cameras for facial, retinal,or other scans, microphones for voice signatures, etc. In conjunctionwith, or separate from, the biometric scanners 225, each computingdevice 200 may include authentication circuitry 230 to allow thecomputing device 200 to engage in, for example, financial transactions(such as mobile payment and digital wallet services) in a more securemanner. Various computing devices 200 may include one or more locationsensors 235 to enable computing device 200 to determine its locationrelative to, for example, other physical objects or relative togeographic locations. Example location sensors 235 include globalpositioning system (GPS) devices and other navigation and geolocationdevices, digital compasses, gyroscopes and other orientation sensors, aswell as proximity sensors or other sensors that allow the computingdevice 200 to detect the presence and relative distance of nearbyobjects and devices. Computing device 200 may also include ambientsensors 240 that allow for the detection of sound and imagery, such ascameras (e.g., visible, infrared, etc.) and microphones, in thesurroundings of computing device 200. A computing device's microphonemay be considered an ambient sensor that could also be used as abiometric scanner if it is involved in capturing the voice of a user forauthentication purposes, and/or a user interface if the microphone isinvolved in receiving information, commands, or other inputs from, forexample, speaking users.

Each computing device 200 may include one or more applications 250(“apps”) that aid the computing device 200 in its operations and/or aidusers of the computing device 200 in performing various functions withthe computing device 200. In some implementations, applications 250 maybe stored in memory 210 and executed using processor 205, and mayinteract with, or otherwise use, one or more of communicationsinterfaces 215, user interfaces 220, biometric sensors 225,authentication circuitry 230, location sensors 235, and/or ambientsensors 240. Not every provider computing device 110, consumer computingdevice 120, advisor computing device 130, and/or third-party computingdevice 140 necessarily requires or includes all of the exampleapplication components/modules depicted in FIG. 2 as being part ofapplication 250.

Example components of one or more applications 250 (running on, e.g.,provider computing device 110, consumer computing device 120, and/oradvisor computing device 130) include a transition module 255 configuredto determine whether or when it is advisable to transition a userbetween robo-advising and human advising based on one or more transitiontriggers (which are further discussed below). For example, thetransition module 255 (running on provider computing device 110 orconsumer computing device 120) may use inputs to determine that it isappropriate to transition a user computing device 120 from robo-advisingto human advising based on one or more human advising triggers, and fromhuman advising to robo-advising based on one or more robo-advisingtriggers. Such “go-human” triggers may indicate that a need or goal of auser is sufficiently complex, variable, unpredictable, or significant soas to warrant input from or review by a human advisor. For example,human advising triggers may indicate that two or more options areavailable for a user, with the options sufficiently divergent (i.e.,having substantially different consequences depending on factors beyondthe purview of the robo-advisor, and/or requiring subjective evaluationof a user's circumstances) to warrant human intervention. Examplego-human triggers may include: a transaction exceeding a threshold value(e.g., investing a large sum of money); a conversation determined toindicate that a situation is very emotionally charged (based on, e.g.,above-average volume for the voice of the speakers, detection of tensionin voices, and/or identification of a major life event); extensivecommunications about a topic, suggesting that the user is weighing manyfactors because a financial issue is significantly nuanced orparticularly personal; use of predetermined keywords or phrasesassociated with topics outside the purview of the robo-advisor;expression of a desire to speak with a professional advisor; etc.Go-human triggers may be identified in, for example, conversations orother communications of the customer with other users and/or with achatbot.

Similarly, the transition module 255 (running on, e.g., providercomputing device 110, user computing device 120, and/or advisorcomputing device 130) may determine, during a communications sessionbetween a customer and an advisor, that the customer may have reached apoint that no longer requires human intervention, or that a return torobo-advising may otherwise be a viable option, based on one or moretriggers for robo-advising. Such “back to bot” triggers may, forexample, indicate that the motivation for transitioning to humanadvising may no longer be relevant (e.g., an issue has been resolved orotherwise sufficiently addressed, one or more accounts have been set upand/or restructured, etc.), that the topics being discussed are all inthe purview of the robo-advisor, and/or that the conversation has becomenon-financial in nature (e.g., the user and advisor have concluded adiscussion of life events or financial situations and are onlydiscussing news or sports). In some implementations, if the topics beingdiscussed during a human-advising session have no go-human triggers(such that if the discussion had been detected outside of the sessionwith the advisor, the robo-advisor would not have determined that humanintervention or review is warranted), then the transition module 255 maydetermine that a return to robo-advising is appropriate. Back-to-bottriggers may be identified in, for example, conversations or othercommunications of the customer with the advisor, such as entries whileinteracting with a user dashboard during a session with the advisor.

An advisor manager 260 may be configured to identify one or moreadvisors that may be able to assist a user based on the user's needsand/or goals, and to schedule a meeting or other communications sessionwith the advisor (by, e.g., comparing the user's and advisor's calendarsto determine mutual or overlapping availability). For example, if one ormore go-human triggers are detected, or it is otherwise determined thatthere is a financial need or goal suited for human advising, the advisormanager may access records stored at a provider computing device 110, anadvisor computing device 130, and/or a third-party computing device 140to determine which advisors may have the background and experiencesuited to the customer's needs and goals. The advisor manager 260 mayalso access records (e.g., transcripts) of prior sessions of an advisor(with the same or with other users) to determine whether the advisorwould be a good match with the user of the consumer device 120. Theultimate suitability of an advisor may sometimes be based, at least inpart, on whether the calendars reveal mutual/overlapping availabilityfor the consumer and the advisor (even if otherwise matched based onneeds and expertise). The advisor manager 260 may access one or morecalendars accessible to one or more consumer devices 120 to determinethe customer's availability. In some implementations, the advisormanager 260 may determine the customer's availability based ondiscussions of the user (e.g., detecting via a consumer device 120 thatthe customer stated “I'm available all day Friday”) or othercommunications. The advisor manager 260 may access one or more calendarsaccessible to provider computing device 110, advisor computing device130, and/or third-party computing device 140 to determine theavailability of one or more advisors. Computing devices withseparately-maintained calendars may interface with each other using,e.g., any combination of one or more application programming interfaces(APIs), software development kits (SDKs or devkits), or otherhardware/software mechanisms that facilitate data exchange orcommunication between and among co-located or remote computing systemswith various access protocols.

A location monitor 265 may be configured to determine the location of,for example, consumers and advisors, as well as the locations associatedwith customer transactions (e.g., where a transaction took place). Thelocation monitor 265 may be configured to track (using, e.g., one ormore location sensors 235) the physical location of computing device200. The location monitor 265 may be configured to identify the locationof the computing device 200 at specified points in time or whentriggered by identified events, such as the location of the consumercomputing device 120 when a purchase occurs, when a device is turned onor off, when an application is launched, etc. The location of computingdevice 200 may be presumed to correspond with the location of one ormore users associated with the computing device 200, and/or the locationat which an event occurred. In different implementations, location maybe determined without using location sensors 235. For example, locationof computing device 200 may be determined by determining the location ofa merchant at which a purchase occurred using a payment app running oncomputing device 200. Additionally or alternatively, location may bedetermined using other sensors, such as ambient sensors 240 used todetect sounds and videos that are recognized as indicative of a certainphysical location of the computing device 200 (e.g., detection of spokenwords or phrases from which location may be inferred, or detection ofsounds from a public announcement system of a particular landmark suchas a train station or airport). Also, a location of a first computingdevice may be determined based on (geographically-limited)communications (such as NFC, Bluetooth, WiFi) of the first computingdevice with a (nearby) second computing device (such another user'ssmartphone, the router of a hotel or restaurant, etc.) for whichlocation has already been determined or is known or presumed.

A chatbot 270 may be configured to simulate a conversation between acustomer and advisor. Such a conversation may be conducted by, forexample, capturing a customer's spoken words (or other communications),analyzing the communication to better understand context and identifyuser needs, and responding to the customer or otherwise providinginformation determined to be relevant. In some implementations, inputs(or a portion thereof) received via chatbot 270 may be fed to analyticsengine 275 for analyses and formulation of responses. Alternatively oradditionally, chatbot 270 may perform the analyses needed to formulatesuitable responses to users. In certain implementations, certainanalyses may be performed by chatbot 270 (e.g., determining what a useris asking and identifying when a financial issue has arisen), whileother analyses (e.g., determining what recommendation would be suitablebased on the financial issue and the user's circumstances, behaviors,etc.) may be performed via analytics engine 275.

The analytics engine 275 may be configured to enable artificial/machineintelligence capabilities by, for example, analyzing customer andadvisor inputs (to, e.g., determine user goals and needs) and generatingrecommendations and proposals for presentation to the customer (to,e.g., achieve goals and/or satisfy needs). The analytics engine 275 mayutilize, for example, artificial intelligence and machine learning toolsto analyze customer conversations or other inputs and otherwise providerobo-advising without human intervention.

A transaction monitor 280 may be configured to identify and keep trackof financial or other transactions of users. A customer may engage intransactions using, e.g., mobile payment and digital wallet services, orvia any app and/or device through which a user may make purchases,transfers, deposits, cash advances, etc. The transaction monitor 280 mayaccess such sources as user accounts (e.g., bank accounts, brokerageaccounts, credit card accounts, merchant accounts, etc.) andpayment/wallet applications to acquire data on transactions. A sessionmanager 285 may be configured to initiate and terminate communicationssessions between consumer computing devices 120 and advisor computingdevices 130. Such advising sessions may incorporate one or more ofaudio, video, and text entries of users and advisors. In someimplementations, advising sessions may be conducted via the samedashboard (e.g., from within the same application) through which theuser is robo-advised. Advising sessions may begin at times scheduled viaadvisor manager 260, and/or on an ad-hoc basis. A profile manager 290may generate and update user and advisor profiles (further discussedbelow), which facilitate robo-advising and human advising and help maketransitions between the robo-advising and human advising smoother.

An external resource module 295 may be configured to access data frominformation sources other than the provider computing device 110 and theconsumer computing device 120. In some implementations, the externalresource module 295 may use, for example, any combination of one or moreAPIs, SDKs, or other hardware/software mechanisms that facilitate dataexchange or communication between and among co-located or remotecomputing systems with various access protocols. Alternatively oradditionally, the external resource module 295 may accesspublicly-available information sources. External resources may includefinancial product websites, merchant websites, and other sources ofinformation on available products. In certain implementations, theexternal resource module 295 may access social networking websites forinformation on, for example, life events and familial or otherrelationships to understand (in an automated fashion) the needs,circumstances, and likely goals of a user (e.g., information on whomight be affected by the financial decisions of a user, such the user'schildren). The external resource module 295 may similarly access othersources of information, such as credit agencies, news sources, financialinstitutions, governmental bodies, etc. Information from such sourcesmay provide inputs to the analytics engine 275 to inform therobo-adviser in making recommendations as to, for example, financialgoals and changes thereto. The information may also be made available tohuman advisors to assist with advising sessions.

Although the above discussion identifies a set of modules that performspecified functions, in various implementations, the above (and other)functions may be performed by any module in the system 100. Functionsperformed by the modules discussed above may be redistributed (i.e.,differently apportioned or distributed) among the modules ofapplications running on provider computing devices 110, consumercomputing devices 120, advisor computing devices 130, and/or third-partycomputing devices. Similarly, the functions discussed may beconsolidated into fewer modules, or expanded such that they areperformed by a greater number of (separate) modules than illustratedabove. For example, functions performed by the above-identified modulesof one or more provider computing devices 110 could additionally oralternatively be performed by modules of one or more consumer computingdevices 120, and functions performed by the above-identified modules ofone or more consumer computing devices 120 could additionally oralternatively be performed by modules of one or more provider computingdevices 110.

Referring to FIG. 3, in example implementations, a system 300 mayinclude a virtual dashboard 310 (see, e.g., FIGS. 8-17 discussed below)that is accessible to one or more consumer computing devices 120 and oneor more advisor computing devices 130. The dashboard 310, which may bemaintained and/or administered using one or more provider computingdevices 110 of a service provider, may be “unified” in the sense that itallows consumer computing devices 120 and advisor computing devices 130to effectively exchange information in the same virtual environment.Because customers and advisors may interact with each other via, forexample, user interfaces with common elements, and both users andadvisors may be able to readily access at least some (if not all) of thesame information and user interface elements, advisors may more easilylearn of a customer's circumstances (goals, needs, etc.) via dashboard310. This may help save consumers and advisors from needing to devote asubstantial amount of resources (time, computing resources, etc.) tobring an advisor “up to speed.” Users need not spend time explainingtheir unique situations by sharing details that have already beenentered or otherwise provided by the user or acquired from variousinformation sources (such as third-party computing devices 140). Acommon dashboard helps discussions by allowing customers and advisors torefer to the same user interface elements. Moreover, familiarity withthe dashboard allows the customer and advisor to more readily access andprovide information that is relevant to different topics being discussedor otherwise addressed. The unified dashboard 310 may help provide forsmoother transitions between robo-advising and human advising.

In certain implementations, the provider computing system 110 maymaintain a user profile (further discussed below) that may includerelevant financial information, user preferences, triggers fortransitioning between robo-advising and human advising, and other data.The provider computing system 110 may use user profiles to assist withthe implementation of dashboard 310. Consumer computing devices 120 canbe provided access to the dashboard 310 to receive recommendations,review conversations, enter additional information, monitor progresstowards goals, request and schedule human advising sessions, etc.Advisor computing devices 130 may be used to access consumer data,schedule advising sessions with consumers, provide additionalrecommendations, monitor and update goals, etc. The user profile mayinclude parameters for what information is accessible, when transitionsare advisable, etc., further helping make transitions smoother.

Referring to FIG. 4, various versions of example process 400 may beimplemented using, for example, a provider computing device 110, aconsumer computing device 120, and an advisor computing device 130. At410, one or more computing devices 200 (e.g., consumer computing devices120 and/or, in some implementations, provider computing device 110) maybe used to capture user inputs. User inputs may include conversations(e.g., spoken conversations or discussions in electronic messages)captured via computing devices 200, entries submitted via application250, or any other transfer or exchange of data from the user to thecomputing device 200. For example, application 250 running on consumercomputing device 120 may detect (using microphones of one or moreconsumer computing devices 120) that a customer is discussing afinancial matter. In some implementations, a provider computing device110 may receive audio of a conversation from a consumer computing device120 for analysis, and/or a consumer computing device 120 may itselfanalyze audio of conversations. In certain implementations, particularkeywords or phrases may be deemed to indicate a potential financial goalor need. Examples include: “my mother had a bad fall . . . I need tomanage her finances”; “my credit score is really low . . . . I need towork on improving my credit score.”; “I would like to buy a car”; “Iwould like to go on a vacation/I need a vacation”; “Honey, we shouldsave some money . . . We should have more of a cushion in our financesin case we have unexpected expenses”; “We're having a baby, we need tostart saving for college”; etc.

Additionally or alternatively, at 420, one or more computing devices 200may access records on financial or other transactions of the user toidentify transactions indicative of a user need or goal (such as babysupply purchases indicative of a potential goal or need to save foreducational expenses). In some implementations, such transactions may bedetected via, for example, application 250 running on, for example, aconsumer computing device 120, such as mobile wallet or electronicpayment application. In various implementations, such transactions maybe identified by, for example, a consumer computing device 120 accessinguser records maintained at or administered by a provider computingdevice 110 (e.g., for accounts held at a provider that is a financialinstitution) and/or accessing a third party computing device 140. Insome implementations, such transactions may be identified by a providercomputing device 110 accessing a consumer computing device 120 and/or athird party computing device 140.

At 430, one or more computing devices (e.g., provider computing device110 and/or consumer computing device 120) may retrieve data from thirdparty computing devices 140 that may be informative of a user'scircumstances. For example, accessing a customer's credit report mayindicate that a customer may need assistance with improving his or hercredit score. Similarly, application 250 (running on, e.g., a providercomputing device 110 and/or a consumer computing device 120) may accesssocial networking applications to identify family members, life events,travel plans, etc. A determination as to which third party data sourcesto access may be based at least in part on user inputs and/ortransactional data. For example, application 250 may detect aconversation about an upcoming trip without an identification of thedestination, or about an upcoming move to a college dorm without anidentification of the college or dorm, and in response a providercomputing device 110 may determine that accessing a third partycomputing device 140 of a social networking source, a college directory,a ticket purchase identified via travel sites, etc., may help identifythe destination, college, and/or dorm.

At 440, the user inputs, transactional data, and/or third party data maybe analyzed by one or more computing devices 200 (e.g., via analyticsengine 275 of application 250 running on a provider computing device 110and/or on a consumer computing device 120) to identify one or morefinancial issues. For example, based on user inputs acquired via aconsumer computing device 120, a provider computing device 110 maydetermine that a consumer could benefit from a financial product or acertain course of action. In response, at 450, the provider computingdevice 110 may present, via an application 250 running on a consumercomputing device 120, a recommendation. The recommendation may be, forexample, to set up an account (e.g., a bank or credit account), divertmoney into one or more accounts for savings, subscribe to a service,etc. If it is determined that the financial issue warrants review orintervention by a human advisor, the recommendation of providercomputing device 110 (presented via, e.g., application 250 running on aconsumer computing device 120) may be to engage with a human advisor(e.g., an advisor generally, an advisor by specialty or expertise,and/or an advisor by name). The advisor manager 260 running on, forexample, a provider computing device 110 and/or a consumer computingdevice 120 may then help the consumer computing device 120 find andconnect with one or more advisor computing devices 130.

If a customer wishes to proceed with human advising, computing device200 (e.g., provider computing device 110 and/or consumer computingdevice 120) may, at 460, facilitate an advising session with a humanadvisor. This may include identifying potential advisors suitable forthe financial issues relevant to the customer's situation (by, e.g., theprovider computing device 110 and/or consumer computing device 120accessing advisor biographies stored at one or more provider computingdevices 110, advisor computing devices 130, and/or a third partycomputing devices 140). In some implementations, facilitating anadvising session with a human advisor may include the computing device200 (e.g., a provider computing device 110) arranging a time for thecustomer to have a discussion with an advisor by accessing calendars onone or more consumer computing devices 120 and advisor computing devices130, and proposing one or more times during which the customer and theadvisor are both available. The provider computing device 110 may theninstruct the consumer computing device 120 and/or advisor computingdevice 130 to update the calendars that are able to be accessed andchanged via the consumer computing device 120 and/or the advisorcomputing device 130. In some implementations, the calendar isadditionally or alternatively maintained on dashboard 310, which may belinked to other calendars accessible to consumer computing device 120and/or advisor computing device 130.

In some implementations, a provider computing device 110 may, fromwithin dashboard 310, connect a consumer computing device 120 with anadvisor computing device 130. This may be accomplished by enabling videochat, audio chat, text chat, or other live interaction sessions. Incertain implementations, the provider computing device 110 may monitorthe communications (e.g., by listening to spoken words) or other dataexchanged during live interactive sessions between customers andadvisors to update customer goals and needs for subsequent use.Monitoring such data can enable the robo-advisor to seamlessly take overfrom advisor computing device 130 when the human advising session isconcluded and advise or otherwise assist the customer (until humanintervention is needed at a future time). In other implementations,provider computing device 110 does not facilitate a live session betweenthe consumer computing device 120 and the advisor computing device 130,and instead subsequently updates a user profile using data obtained viaother channels after the session has concluded. Such data may beobtained by, for example, capturing user inputs (410) (e.g., bylistening to a conversation about the session between the customer andanother person), accessing transactional data (420), and/or acquiringdata from third party source (430).

Referring to FIG. 5, an example process 500 for transitioning betweenrobo-advising mode 510 (on left side) and human advising mode 520 (onright side) is depicted. At 530, provider computing device 110 surveilsconsumer computing devices 120 and third party computing devices 140 toidentify financial issues and changes in/updates to a customer'scircumstances. As discussed above, this may be accomplished, forexample, via channels that allow for monitoring of communications (e.g.,by detecting conversations via a chat bot and/or scanning electronicmessages to extract relevant data). Based on the data acquired via suchsurveillance, at 535, provider computing device 110 and/or consumercomputing device 120 may determine a strategy and present (via, e.g.,application 250 running on the consumer computing device 120) one ormore recommendations. Based on inputs (e.g., one or more “go-human”triggers), at 540, the provider computing device 110 and/or consumercomputing device 120 may determine that human advising is desirable andrecommend a session with a human advisor. At 545, the provider computingdevice 110 and/or the consumer computing device 120 may then identifysuitable advisors and schedule a communications session with an advisorcomputing device 130.

The provider computing device 110 may then, at 550, initiate a livecommunications session (e.g., with video, audio, and/or text chatting)between the consumer computing device 120 and the advisor computingdevice 130. Based on the communications between the consumer computingdevice 120 and the advisor computing device 130, provider computingdevice 110 may, at 555, update or otherwise revise the profile,financial goals, and strategies of the customer (stored at, e.g., theprovider computing device 110, the consumer computing device 120, theadvisor computing device 130, and/or the third party computing device140). At 565, the provider computing device 110 may then, in response toa command from the consumer computing device 120 and/or from the advisorcomputing device 130) terminate the live human advising session andreturn the customer to robo-advising mode 510.

In some situations, the customer may receive the help that warranted ahuman advisor, but the human advising session is not terminated(because, e.g., topics to be discussed were added during a session,because the topics of discussion were too broad to begin with, etc.).The advisor may then be spending time with a customer in human advising520 even though the customer could be served just as well viarobo-advising 510. The provider computing device 110 and/or advisorcomputing device 130 may, in some implementations, monitor thecommunications between the user computing device 120 and the advisorcomputing device 130 for “back to bot” triggers, or to otherwisedetermine when the human advisor may no longer be needed, or when thecustomer has reached a point at which the provider computing device 110may be able to assist the customer using automated tools. The providercomputing device 110 and/or advisor computing device 130 may (via, e.g.,dashboard 310) present a virtual button, link, “pop up” notification orother message, etc. (see, e.g., FIG. 11), to inform the advisor that oneor more matters suspected to be addressable via robo-advising have beenidentified and/or to otherwise allow the advisor to initiate a “handoff”back to the robo-advisor. In some implementations, such a selectionterminates the human advising session. In other implementations, such aselection additionally or alternatively sends a message to consumercomputing device 120 with an option to terminate the advising sessionand/or a list of one or more topics or selections for issues to address(e.g., enter requested information on financial accounts, income, bills,etc.) outside of the communications session (e.g., in an automatedfashion).

Advantageously, this can enhance efficiency and save the time of boththe advisor and the consumer by using the type of interaction (roboversus human) suited to the stage of advising or the particular issuesto be addressed. For example, having a human advisor waiting while theprovider computing device 110 and/or the consumer computing device 120collects information (e.g., account numbers, etc.) may not be an idealuse of the advisor's time. Similarly, having a customer waiting as theadvisor computing device 130 retrieves information on a set of availableoptions when the set can be generated by the robo-advisor (potentiallymore quickly) may not be an ideal use of the customer's time.

Referring to FIG. 6, illustrated is an example profile 600 that may, incertain implementations, be generated and/or maintained by providercomputing devices 110 for use by provider computing devices 110,consumer computing devices 120, and/or advisor computing devices 130.This profile may be saved in memory as database records, data packets,text files, or in other suitable formats.

As discussed above, a transition module 255 may determine that it isappropriate to transition a user computing device 120 from robo-advisingto human advising to better assist a customer. To facilitate suchdeterminations, profile 600 may include go-human triggers 605 (discussedabove) to assist with the identification of a situation in which a humanadvisor may be suitable. Go-human triggers 605 may, for example, beunique to the specific customer based on past behaviors (e.g., if acustomer has sought human assistance when a certain issue arises, theissue/behavior may indicate a go-human trigger 605). Triggers 605 mayalso include customer inaction in response to certain life events and/orin response to certain recommendations in situations (which may beunique to a customer) deemed to be significant enough to warrant actionsooner rather than later (based on, e.g., certain detected inputs).

Similarly, the transition module 255 may determine a return torobo-advising may be appropriate based on back-to-bot triggers 610(discussed above). Back-to-bot triggers 610 may be based on, forexample, certain behaviors of the customer. For example, if a customeris detected to routinely (and in a sufficiently timely manner) handlecertain financial situations without advising sessions with advisorcomputing devices 130, then identification of the financial situationmay be a back-to-bot trigger that indicates it may be suitable to allowthe customer to continue on a robo-advising track or otherwise withouthuman discussion for the time being. Back-to-bot triggers mayalternatively or additionally be based on a customer's savviness,expertise, or familiarity with certain situations. For example, if acustomer is determined to be sophisticated with respect to certainfinancial situations, then identification of the corresponding financialsituations may indicate that robo-advising may be suitable. In someimplementations, a customer's savviness or ability to handle a situationmay be determined, for example, via an evaluation (e.g., using analyticsengine 275 running on provider computing device 110, consumer computingdevice 120, and/or advisor computing device 130) of the customer'ssophistication with respect to certain issues. Sophistication may bebased on, for example, how advanced the language used by the customer iswith respect to an issue. For example, a customer who is detected todiscuss available options with respect to a certain financial situationwith a family member may be deemed more sophisticated than a customerwho is detected only to discuss the circumstances of the financialsituation with no talk of viable options for how the customer mayproceed. Sophistication (in general or specific to financialissues/situations) may be stored in one or more fields of profile 600 tohelp with advising generally and to help make transitions betweenrobo-advising and human advising more effective.

In certain implementations, fragmented issue indicators 615 may be usedto allow provider computing device 110 and/or user computing device 120to track and connect inputs over time (as being related or otherwise asbuilding upon each other to form a better picture of circumstances orotherwise better inform advising). In some situations, a person's needsor goals do not become apparent in one conversation, statement,communication, transaction, or other act. For example, the keywordsand/or phrases that indicate a user has a certain need or goal may notbe detected as part of a single conversation or otherwise within a shortperiod of time. Needs or goals may unravel over time (hours, days,weeks, months, etc.) as a consumer obtains more information and/orcontemplates his or her situation based on new events and availableinformation. And the bases for such goals and needs may go unexpressedor otherwise remain unapparent for some time.

For example, a consumer device 120 may detect a customer explaining to afriend that his or her mother had a bad fall, and may detect, in aseparate conversation with his or her sibling, the customer explaining“I need to manage her finances.” Separately, these inputs may beinsufficient to identify a financial goal or need and make a goodrecommendation. However, when considered together, these two inputs maybe deemed (by, e.g., analytics engine 275) to indicate that a user mayneed certain financial assistance or have a certain financial goal. Theconsumer computing device 120 (and/or the provider computing device 110using audio or other data received via consumer computing devices 120)may (based on, e.g., detected keywords, phrases, or other signals)determine that a piece of information may potentially be relevant towhether a financial goal or need exists. If such a signal is detected,the provider computing device 110 and/or user computing device 120 mayrecord such a signal as a fragmented issue indicator 615. Then, when asecond signal that is similarly determined to include a piece ofinformation that is potentially relevant to some financial issue isdetected, the provider computing device 110 and/or consumer computingdevice 120 may access profile 600 for fragmented issue indicators 615that may be relevant. If such a related fragmented issue indicator 615is in the user's profile 600, the robo-advisor (via, e.g., the providercomputing device 110 and/or the consumer computing device 120) maydetermine that there is a likely need, and generate an appropriaterecommendation, or determine that more information (e.g., additionalsignals or inputs) is needed to generate a relevant or usefulrecommendation.

In the above example, the consumer computing device 120 and/or providercomputing device 110 may identify a first signal when a phrase such as“my mother had a bad fall last night” is detected. In someimplementations, application 250 may first process the signal to givethe signal more meaning or clarity and/or to supplement the signal withadditional information. For example, analytics engine 275 running onprovider computing device 110 may analyze the phrase and retrieveinformation from various sources to determine who was involved (e.g.,who is the speaker's mother based on user records or third partysources), on what date the fall occurred (e.g., what is the date of theday before the day on which the signal was detected), what can bepredicted about the fall in the context of the conversation (e.g., ifthe speaker's voice indicated that the speaker was upset, the fall maybe deemed to have been more serious or more recent than if the speaker'svoice indicated the speaker was apparently nonchalant about theincident), what a “bad” fall might mean for a person of the mother's ageor other known or determinable circumstances (e.g., the mother's age orwhether such falls have occurred in the past), etc. Such information maybe in the user's record or determinable from third party sources (e.g.,from sources of medical information), and the fall may be deemed moreserious based on certain criteria (such as the mother's age being abovea certain age threshold, or the mother suffering from certain conditionsassociated with low bone density, etc.). In various implementations,signals (detected via, e.g., provider computing device 110 and/orconsumer computing device 120) need not be limited to expressions (e.g.,spoken conversations, written discussions, or other communications).Additionally, signals may be actions taken (using, e.g., consumercomputing device 120), such as opening certain accounts, making certainfunds transfers, making certain purchases, and/or traveling to certainlocations (such as car dealerships, open houses, baby supply stores,assisted living homes, hospitals in general, specific clinics ordoctors' offices with certain specialties, accountants' offices), etc.

The provider computing device 110 and/or consumer computing device 120may record a fragmented issue indicator 615 following the first signalin the profile 600. In various implementations, fragmented issueindicator 615 may state, for example, a derivation of the communicatedphrase (e.g., “family member had an accident,” “user's mother had afall,” etc.), the phrase itself (i.e., “my mother had a bad fall lastnight”), or a supplemented or otherwise revised version of the phrase(e.g., “my mother had a bad fall [on mm/dd/yyyy],” “[user name's]‘mother had a bad fall’ on mm/dd/yyyy,” or “[mother's name] ‘had a badfall’ on mm/dd/yyyy”).

Where the fragmented issue indicator 615 arises from detection of alocation of the consumer computing device 120, the fragmented issueindicator 615 may include an identification of the location visited,such as “customer visited open houses at [home 1] and [home 2]” or“customer visited assisted living home [at address].” In someimplementations, the identification of the location may be accompaniedby an indication of the amount of time spent at the location, such as“customer spent [amount of time] at an assisted living home.” In certainimplementations, a visit to a location may not be deemed significantenough to warrant recording a fragmented issue indicator unless theconsumer computing device 120 was detected to have remained at thelocation for a certain minimum amount of time. For example, a fragmentedissue indicator 615 may not be triggered unless the consumer computingdevice 120 was detected to have remained at a relevant location aminimum of 10 minutes. In some implementations, an analytics engine 275may decide whether to include a fragmented issue indicator 615 inprofile 600 by balancing the likely relevance of a statement or alocation visited, the amount of time spent at the location, and/or thelikely impact on advising or needs and goals of the customer.

In some versions, fragmented issue indicators 615 may be saved as acompilation of, or otherwise associated with, multiple fields. Forexample, there may be a “subject” or “primary” field that may bepopulated with a phrase or derivations thereof, identification ofcertain actions, or other signals. Additional example fields include:time and/or date an input was captured and/or added to profile 600;which computing device was used to capture an input; identity of a userassociated with the computing device used to capture an input; locationof the computing device used to capture an input; identify of thespeaker or source of the input; etc. In some implementations, these maybe used to give meaning to fragmented issue indicators 615 orcombinations thereof.

In some implementations, a user's profile 600 includes fragmented issueindicators 615 associated with multiple users. The names of other users(e.g., family members, confidants, etc.) with whom a user is associatedmay be included in profile 600 (e.g., in goals and progress 625), andfragmented issue indicators 615 may be stored in multiple profiles 600such that any single profile 600 may include the fragmented issueindicators 615 of all associated users. For example, a first user'sprofile 600 may include fragmented issue indicators 615 of a second user(and vice versa) who is a family member, friend, or otherwise associatedwith the first user. Signals acquired from multiple individuals (storedin one or more profiles 600) may then be used by, for example, providercomputing device 110 and/or consumer computing device 120 to generaterecommendations.

As an illustrative example, a first signal may be based on a first inputresulting from a first user (e.g., an adult child) saying “I need tomanage her finances.” A second signal may be based on a second inputfrom a second user (e.g., a parent of the adult child) saying “I had abad fall.” A third signal may be based on detection of the consumercomputing device 120 being located at an assisted living home for morethan 30 minutes. These three inputs may be used to generate threefragmented issue indicators 615 that, together, identify a financialgoal of a person wishing to manage another's finances based on theother's needs. Advantageously, inputs related to one user'scircumstances, goals, needs, etc., may be more accurately and/or quicklyidentified by acquiring and considering inputs from multiple usercomputing devices 200 associated with multiple other users (who maycommunicate about each other even if not directly speaking or otherwisecommunicating with each other). The fragmented issue indicator 615 (aswell as any of the other parameters in profile 600) may also include anaccess permissions field that identifies which fields (if any) of thefragmented issue indicator 615 (or other parameter corresponding to theaccess field) are accessible to particular advisors or other users.

In some implementations, a recommendation from the robo-advisor may bebased on one or more fragmented issue indicators 615. Additionally oralternatively, the provider computing device 110 and/or user computingdevice 120 may await a second (or third, fourth, etc.) signal that isrelevant to the first signal (or one or more prior signals if more thanone) and allows for a more informed or more targeted recommendation.Continuing with the above example, if the user computing device 120detects “I need to manage her finances,” application 250 may determinethere is a potential financial issue (based on, e.g., keywords such as“manage” and “finances”) but may also determine that more information isdesirable for formulating a suitable recommendation. Such informationmay, in some implementations, be acquired via dialogue with the customer(e.g., an inquiry, conversation, or other information exchange). Forexample, chatbot 270 of application 250 (running on, e.g., a consumercomputing device 120) may speak with the customer to ask generalquestions (e.g., inquiring whether the customer would like assistancewith a financial issue, followed by more specific questions) and/orspecific questions (e.g., inquiring whether the customer would like tomanage all finances or only finances related to certain expenditures,such as health care).

In certain implementations, when the second third, or other signal isdetected, the provider computing device 110 and/or user computing device120 may access the fragmented issue indicators 615 for relatedinformation. Based on, for example, one or more signals (related to themother's fall), application 250 may predict that the person who is tohave her finances managed (corresponding to the term “her” in astatement) is the mother's, and the reason for the management offinances might be a “bad fall.” The robo-advisor (via, e.g., providercomputing device 110 and/or user computing device 120) may then be moreinformed about subsequent signals (e.g., that the fall will besubsequently discussed and additional details can be extracted fromthose subsequent conversations), provide more informed recommendations,or ask more informed questions as part of a dialogue with the customer.Alternatively or additionally, the second signal may be recorded asanother fragmented issue indicator 615 for subsequent use (e.g., incombination with a third signal detected subsequently).

In some implementations, the fragmented issue indicators 615 may be madeavailable to an advisor computing device 130 prior to or during a humanadvising session. Such fragmented issue indicators 615, or certainfields therein, may be recorded using, for example, “plain” text orother format that is readily interpretable by a financial advisor tohelp make the transition from robo-advisor to human advisor moreefficient by helping the advisor more quickly understand the customer'scircumstances (and consequent needs and goals). In some implementations,the user profile 600 may record encoded versions of the signals asfragmented issue indicators 615, and the decoding scheme may be madeaccessible to specified advisor computing devices 130 or other devicesto help control what information is shared (to save time that mightotherwise be spent reviewing information that is not particularlyrelevant to a topic to be discussed during an advising session, tobetter maintain confidentiality of certain information, etc.).

This approach assists with implementation of pervasive advising, as amore complete picture can be formed even though computing devices 200may only detect or acquire part of the picture (e.g., aspects of acustomer's circumstances) in a given time period. Multiple segments of adiscussion, user entries, etc., in multiple contexts, may be needed ordesired to enhance understanding of relevant financial issues and thusenhance the likely value and relevance of resulting recommendations.Advantageously, user computing devices 120 being used to detectconversations may not always detect a conversation in its entirety, oreven if a whole conversation is detected, not all of the words andmeanings may have been understood. For example, if the user computingdevice 120 detecting a conversation is a smartphone, and the smartphoneis placed in a pocket or bag during a conversation, the voices maybecome muffled, and the portion of the conversation during which thesmartphone is in the pocket or bag may be missed. Similarly, if the usercomputing device 120 is a smart speaker in one room, and one or morespeakers move out of the room or otherwise out of the range of the smartspeaker, portions of the conversation may be missed. By combiningfragmented issue indicators 615, a customer's needs can be evaluated andidentified over time as additional user inputs are detected.

Example profiles 600 may also include one or more fields related toexclusions and deferments 620. These fields may indicate, for example,that a customer does desire or need assistance with certain matters(exclusion of a matter), or may not desire or need assistance for acertain specified time period (deferment of matters). In someimplementations, application 250 may refer to exclusions and deferments620 before a recommendation is formulated or given. For example,conversationalists (via spoken words, written communications, etc.) maymake certain statements in certain contexts that are not, taken inisolation, valuable predictors of a user's goals or needs. For example,a speaker may make a statement with a friend for the purpose of making apoint, in jest, sarcastically, to be agreeable, and/or to sparefeelings. In a hypothetical, if a friend informs a customer that thefriend has not done nearly enough to save for the friend's child'seducation, and, so as to be agreeable, the customer states that thecustomer has similarly not done nearly enough, the customer does notnecessarily need help with the financial goal of saving for thecustomer's child's education. The customer may not be prioritizing theparticular goal, or may have already established the goal and be makingprogress towards it (as can be confirmed by application 250 accessingthe customer's accounts, prior advising sessions, other communications,etc.), consequently, the customer may not need to immediately address orrevisit the issue. In some implementations, such a statement may bedeemed to warrant an entry in exclusions and deferments 620 of thecustomer's profile to help limit or avoid recommendations on certaintopics. Similarly, an exclusion and deferment 620 may be generated inresponse to a specific instruction or statement of a customer (e.g., acustomer stating to a consumer computing device 120 directly or making astatement to another person such as “I do not want to be advised on thistopic” or “that's not a priority of mine right now, I will deal withthat next month/year”). In some implementations, the information onparticular topics may still be saved to help form a better picture of acustomer's circumstances, but recommendations may be modified to avoidor delay certain topics.

Alternatively or additionally, certain statements may be analyzed togenerate entries in goals and progress 625 of profile 600. For example,continuing with the above example, the customer saying that he or shealso has not done nearly enough to save for college may indicate that,for example, the customer has one or more children (if not already knownor determined in another way), that the customer may be consideringcollege savings (especially if the customer has not already been advisedon this topic), and/or that the customer may deem college savings apriority or otherwise a relevant consideration in making financialdecisions in the future. Such information, recorded in profile 600, maythen be used by the robo-advisor, and/or presented to an advisor, tobetter inform recommendations and proposals.

Profile 600 may also include one or more session parameters 630.Application 250 (via, e.g., consumer computing device 120) may acceptsession parameters 630 (via, e.g., dashboard 310) to determine how ahuman advising session should be conducted. For example, a customer maywish to have audio only, text only, or video chat. The sessionparameters may be used by provider computing device 110, user computingdevice 120, and/or advisor computing device 130 to provide the customerwith human advising sessions that meet the customer's needs.

Additionally, a customer may only wish to receive automatedrecommendations in specified ways, something that can be indicated inrobo-advising parameters 635 of profile 600. In some implementations,the consumer computing device 120 may be programmed to only speak orotherwise make inquiries and provide recommendations under certainconditions but not under other conditions based on robo-advisingparameters 635. For example, if a user is speaking with a casual friend,it may not be appropriate to converse with the user to inquire as towhether the user wishes to pursue a specified (personal/confidential)financial goal that is identified based on the conversation with thecasual friend. Rather, the user may wish to receive recommendations whenthe user is alone, at home, with close family or friends only, duringcertain times and days (e.g., not during work hours, or not after dinnerwhen the user may be winding down for sleep and not wishing to considerfinancial issues, or not on Sundays), and via certain channels andformats. In some implementations, robo-advising parameters 635 may, forexample, prohibit a smart speaker or other consumer computing device 120from disrupting the customer or discussing confidential topics atinappropriate times.

Profile 600 may also include human advising parameters 640. In someimplementations, human advising parameters 640 may indicate that acustomer wishes only to receive high-level advice on overall goals fromhuman advisors (e.g., to discuss the “big picture”). Similarly, thehuman advising parameters 640 may indicate that the customer isadditionally or alternatively interested in more specific advice onimplementing particular goals or executing on action plans. In certainimplementations, the fields/values of human advising parameters 640 maybe used by provider computing device 110 and/or customer computingdevice 120 when matching a customer with a suitable human advisor.

Profile 600 may additionally or alternatively include one or moreacquisition parameters 645. In one or more fields, acquisitionparameters 645 may specify how the customer is to be surveilled (e.g.,what inputs may be acquired, how various inputs are captured, etc.) andwhen/where the customer is not to be surveilled. In someimplementations, acquisition parameter 645 may indicate which consumercomputing devices 120 may be used to detect conversations. For example,a customer may wish to include/exclude detection of conversations viaidentified smartphones, smart speakers, smart watches, laptops, etc., tocontrol in what circumstances the customer's words may be taken intoconsideration (e.g., should or should not be used as a source of datafor advising purposes). Consumer computing devices 120 may be identifiedby, for example, device identification numbers and/or associated users.In various implementations, acquisition parameter 645 may, alternativelyor additionally, identify certain locations (as determined using, e.g.,location sensor 235) which are “off limits” and conversations should notbe surveilled. For example, a customer may identify a doctor's office asa location, and in response to detection that the consumer computingdevice 120 is located in, or has moved into, the identified location,the consumer computing device 120 may cease detection of conversationsfor use in advising the customer. This would allow the customer toexclude certain private conversations (with, e.g., a therapist) fromconsideration in advising. In some implementations, acquisitionparameters 645 may be used to indicate that conversations with certainpersons are included/excluded as advising inputs, and/or certain modesof communication are included/excluded as advising inputs. With suchacquisition parameters 645, a consumer computing device 120 may, forexample, not continue detecting a conversation in response toidentification of a specified speaker (by, e.g., recognizing a voicesignature, detecting the person's name used in a greeting, etc.), and/ormay include exclude certain electronic messages (e.g., text messagesand/or e-mails) received from specified applications and/orcommunication channels from being analyzed for inputs relevant toadvising of the customer.

Parameters and fields corresponding to profile 600 identified in FIG. 6help both the robo-advisor and the human advisor provide more relevantrecommendations in a personalized fashion, while more quickly focusingon the topics on which a customer wishes to receive assistance. Theyalso help customers more seamlessly transition between robo-advising andhuman advising, allowing the more efficient form of advising to be usedbased on customers' circumstances.

Referring to FIG. 8, an example graphical user interface of, forexample, a potential dashboard 310 is illustrated. The user interface,which may be viewable via consumer computing device 120 and/or advisorcomputing device 130, simultaneously or at different times, providesinformation on financial goals. The issues may have been identified andrefined via robo-advising, human advising, or both. Also identified inthe example user interface are accounts held by, or otherwise accessibleto or viewable by, the customer. These accounts may be used in thefulfilment of financial goals, such as by having provider computingdevice 110 and/or customer computing device 120 transfer funds to/fromsuch accounts or control spending by using credit accounts withparticular limits, for certain expenses, etc.

The user interface may also identify advisors which whom the customerhas conferred. In various implementations (not shown in FIG. 8), theinterface may also identify, for example, the topics discussed with eachadvisor, the availability of each advisor, or the recommendations ofeach advisor. Also identified in FIG. 8 are the family members of thecustomer. If authorization is obtained from the family members, even ifthey are not customers or otherwise being separately advised,conversations or other inputs of the family members may be used tobetter understand the goals and needs of the customer and therebyenhance the quality of recommendations and transitions betweenrobo-advising and human advising. Some or all of the information indashboard 310 may be stored or identified in profile 600. For example,fragmented issue indicators 615 for all of the known family members maybe included in profile 600.

In various implementations, any of the icons or screen elements in thefigures can be structured to be clickable or otherwise selectable (usingany input mechanism, such as a touchscreen, mouse, voice prompt,gesture, etc.) for accessing additional information (such as detailsabout an advisor, account, goal, etc.) for initiating communications(with, e.g., one of the advisors or family members), etc.

With reference to FIG. 9, which depicts an example communication betweena consumer computing device 120 and a provider computing device 110 oran advisor computing device 130, in some examples, a person (e.g., acustomer) may have difficulty keeping track of his or her finances andmanaging his or her credit. The person may be expecting to expand his orher family and wish to get his or her finances under control in order tomeet a financial goal of, for example, purchasing a new vehicle inanticipation of expanding the family. In some examples, based on recenttransaction history indicating the possibility of a new baby and/or atransaction such as a newly established college fund, the providercomputing device 110 may pervasively inquire, via a consumer computingdevice 120 (e.g., a proactive listing bot), whether the person wouldlike some help with meeting a financial goal. The financial goal mayinclude buying a new car, establishing good credit, etc. The consumerdevice 120 may listen and interpret the voice input of the person thatindicates a desire to meet a financial goal. In some examples, theprovider computing device 110 may pervasively inquire, via a consumercomputing device 120, whether the person would like to set up a virtualmeeting (e.g., a session or an appointment) with a banker to discuss thefinancial goals of the person. After the customer confirms that he orshe is interested in a session with an advisor, the provider computingdevice 110 may generate a command structured to add the virtual meetingto a calendar accessible to consumer computing device 120 associatedwith the customer and/or a calendar accessible to advisor computingdevice 130 of an advisor, as shown by the calendar and/or schedule icon(“April 15”) in FIG. 9.

In some embodiments, the provider computing device 110 may be part ofthe computing system of a financial institution. Generally, thefinancial institution provides financial services (e.g., demand depositaccounts, credit accounts, etc.) to a plurality of customers. Thefinancial institution provides banking services to the customers, forexample, so that customers can deposit funds into accounts, withdrawfunds from accounts, transfer funds between accounts, view accountbalances, and the like via one or more provider computing devices 110.

Returning to FIG. 7, a flow diagram of a method 700 of providing aproactive listening bot structured to generate an expense strategy isdescribed according to an example embodiment. The expense strategy mayinclude a financial plan, budget, or combination thereof. In somearrangements, the expense strategy may be generated and/or provided inreal-time or near real-time. In some arrangements, the expense strategymay include transaction data, account data, etc. from a plurality ofaccounts of a customer that are spread across multiple financialinstitutions that may or may not be affiliated with the financialinstitution.

Prior to the provision or engagement of a proactive listening botstructured to generate an expense strategy, a user may be authenticatedto the provider computing device 110 and/or consumer computing device120 at 705. In some examples, prior to allowing the user to engage withthe proactive listening bot, the user may be authenticated as an accountholder. The user may be authenticated based on the authenticationcredentials of that user. In arrangements in which the consumercomputing device 120 includes an application 250 associated with theprovider computing device 110, the consumer computing device 120 mayreceive and transmit user authentication data (e.g., data indicative ofthe identity of a customer/member of the financial institution and/or auser of various systems, applications, and/or products of the financialinstitution) to, for example, authentication circuitry 230. In sucharrangements, the user can be identified and authenticated based on theapplication of the provider computing device 110 such that the provisionof additional identification information or account information by theuser is not required. The user authentication data may include any of apassword, a PIN (personal identification number), a user ID, an answerto a verification question, a biometric, an identification of a securityimage, or a combination thereof.

At 710, the provider computing device 110 and/or consumer computingdevice 120 detects a voice input (e.g., a voice trigger, voice key,etc.) indicative of a financial goal. For example, a user (e.g., acustomer, potential customer, other person, etc.) may be contemplatingbuying a new car. The provider computing device 110 and/or consumercomputing device 120 may learn that the user is contemplating buying anew car through active listening to the conversations and/or voice of auser. For example, the user may say “I want to purchase a new car,” “Iwant to save for a home,” etc. The provider computing device 110 and/orconsumer computing device 120 may be structured to monitor user accountinformation, user financial information, spending patterns, etc. of theuser and receive, retrieve, or otherwise access transaction data (e.g.,data indicative of a financial goal such as a transaction, an upcomingtransaction, purchase, other financial data, etc.) based on the voiceinput (e.g., the conversation) of the user.

The consumer computing device 120 may provide advice or otherwise makesuggestions to the customer. In some arrangements, the consumercomputing device 120 may utilize speech recognition and natural languageprocessing to detect the voice input and/or to receive such transactiondata. In some arrangements, the consumer computing device 120 may engagein conversation, discussion, or dialogue with the user to learn moreabout the financial goal and to generate an expense strategy that may beof interest to the user.

In some examples, the consumer computing device 120 may be structured toask the user questions or otherwise request feedback from the user, suchas, “how much do you want to pay for the new car?, how much would youlike the monthly loan payment to be?,” etc. Responsive to the request,the user may provide a voice input (e.g., the user may answer thequestion provided by the consumer computing device 120, providefeedback, or otherwise engage in conversation with the consumercomputing device 120). In some implementations, the consumer computingdevice 120 may be structured to receive a voice input from a pluralityof users and distinguish the voice input associated with the user fromthe voice input or sound associated with another person or user.Alternatively or additionally, the provider computing device 110 and/orconsumer computing device 120 may learn that the user is contemplating afinancial goal (e.g., purchasing a new car) via an advisor computingdevice 130 of an advisor who may be assisting the user with financialplanning, or through other suitable channels.

In some implementations, while the user is engaged in conversation withthe consumer computing device 120, the provider computing device 110and/or consumer computing device 120 may generate an expense strategystructured to meet the financial goal. Alternatively or additionally,the provider computing device 110 and/or consumer computing device 1120may generate an expense strategy structured to meet the financial goalin response to receiving transaction data. For example, the expensestrategy may be generated based on one or more user accounts (e.g., asingle account or a plurality of accounts of the user) associated withthe financial institution.

At 715, the connected device may be structured to provide an expensestrategy structured to meet the financial goal in response to thedetection of the voice input. For example, the consumer computing device110 may output suggestions for meeting the financial goal such as, butnot limited to, the creation of a savings goal, a savings plan to meetthe financial goal, an investment portfolio, a savings strategy, etc. Inthe present example, while listening to a conversation of the user, theconsumer computing device 120 may detect that the user is interested inthe financial goal of purchasing a new car. In response, providercomputing device 110 and/or consumer computing device 120 may generate afinancial plan, budget, investment strategy, or combination thereof tomeet the financial goal of purchasing a new car. The expense strategymay be audibly output from speakers included with or communicativelycoupled to the consumer computing device 120. Alternatively oradditionally, the expense strategy may be displayed via a mobileapplication, an in-app message, a social media application, etc.

The provider computing device 110 and/or consumer computing device 120may include or may be communicatively coupled, via one or more APIs, toa third party computing device 140. The third party computing device 140may be structured to provide relevant data associated with financialgoal of the user. The relevant data may be utilized to generate anexpense strategy comprising various options or suggestions determined tomeet the financial goal of the user. In this regard, the providercomputing device 110 and/or consumer computing device 120 may becommunicatively coupled to a third party computing device 140 structuredto provide such data as inventory data and costs of, for example, a car.

In some examples, there may be a time period between the receipt of thevoice input and the generation of an expense strategy such thattransaction data, the voice input, etc. may be stored for later useand/or retrieval. Accordingly, the user may have expressed an interestin the financial goal (e.g., the purchase of a new car, home, property,etc.) minutes, hours, days, or months ago such that the voice input,transaction data, etc. may be stored in, for example, profile 600.Later, the voice input, transaction data, etc., may be retrieved orotherwise accessed by the provider computing device 110 and/or consumercomputing device 120 for generation of an expense strategy and/or loan(e.g., an offer to accept a loan) as described herein. For example, theuser may have expressed an interest in purchasing a new car severalmonths ago when the desire was not urgent or otherwise was not apriority. When the consumer computing device 120 listens to theconversation of the user and detects that the user is now expecting tohave a baby, the voice input, transaction data, etc., may be retrievedor otherwise accessed to generate a recommendation.

In some arrangements, the consumer computing device 120 may bestructured to detect the urgency of a financial need. Based on thedetection of a voice input indicative of an urgent need financial need(e.g., “We are going to have another child, I need a new car!”), theprovider computing device 110 and/or consumer computing device 120 maygenerate a financial plan, budget, investment strategy, or combinationthereof to meet the financial goal (e.g., the goal to purchase a newcar) that is more aggressive, time restrictive, etc. than a financialgoal associated with a non-urgent need. In some implementations, theurgency of a suspected need may be identified in profile 600 (e.g., aspart of one or more urgency or timetable fields of goals and progress625) based on the voice or words of a customer. Additionally oralternatively, fragmented issue indicators 615 of profile 600 mayinclude a field that characterizes urgency (based on statementsindicating urgency, such as “we need a new car this month” or on othercontextual information) and/or how much emotion was detected in astatement. The provider computing device 110 and/or consumer computingdevice 120 may include speech recognition and natural languageprocessing algorithms that detect, calculate, or otherwise determine thespeed, tone, aggression, etc., of user speech to detect a voice inputindicative of, for example, an urgent need financial need. Suchindicators may also be provided to advisor computing devices 140 toinform, for example, how sensitive or emotionally-charged a topic mightbe for the customer being advised.

At 720, the provider computing device 110 and/or consumer computingdevice 120 may be structured to determine whether to connect theconsumer computing device 120 to an advisor computing device 130 basedon the expense strategy. In this regard, the consumer computing device120 may inquire whether the user would like to set up a session or anappointment (e.g., a virtual session, appointment, meeting, etc.) withan advisor (e.g., a banker) to discuss an expense strategy and/or thefinancial goals of the user. For example, the consumer computing device120 may ask the user if the user would like some help with obtainingcredit for a new car and ask whether the user would like the consumercomputing device 120 to connect with an advisor computing device 130 nowor set up a session with the advisor computing device 130 for later?

After the user confirms that he or she is interested in a session withan advisor, the consumer computing device 120 may initiate a virtualmeeting between the user and an advisor. The consumer computing device120 and/or advisor computing device may receive and/or retrievetransaction data associated with the user from the provider computingdevice 110 and/or a third party computing device 130. In turn, theconsumer computing device 120 and/or advisor computing device 130 mayprovide the transaction data via dashboard 310.

FIG. 10 depicts an example graphical user interface of a potentialdashboard 310 structured to provide robo or human advising according toexample embodiments. The consumer computing device 120 may output, viathe graphical user interface, a user profile 1005 associated with theuser based on, for example, transaction or account data. The userprofile 1005 may identify the user and provide relevant informationpertaining to the user (e.g., user name “Nancy Isau,” customer status“Customer Since 2012,” etc.). In some examples, the graphical userinterface may include or otherwise display data and interactions (e.g.,conversations, transactions, and/or other relevant data) as representedby icons and/or graphics 1010 that have been compiled by the providercomputing device 110 and/or consumer computing device 120 for that user(e.g., the customer's photograph). This may allow a human advisor toseamlessly start the session with the user where the consumer computingdevice 120 and advisor computing device 130 ended a priorconversation/engagement. The dashboard 310 may also provide a “Return toRobo-Advising” selection 1015 to end the session and return the customerto robo-advising. In some implementations, this selection only becomesavailable when “back to bot” triggers are detected.

FIG. 11 depicts an example graphical user interface of a dashboard 310according to example embodiments. The provider computing device 110and/or consumer computing device 120 may be structured to generate anexpense strategy according to a time period (e.g., a timeline, one ormore minutes, hours, days, years, etc.). During the session (e.g., thevirtual robo-advising session with provider computing device 110 orhuman advising session with advisor computing device 130), the advisormay develop an expense strategy that may be implemented over, forexample, a certain period of time based on one or more financial goals.The expense strategy may include one or more icons and graphicsstructured to represent, for example, a “5 Year Timeline” and/orfinancial goals of the user. In some arrangements, the graphical userinterface may include an image and/or video of an advisor, or audio ofthe voice of an advisor. The image, video, and/or the audio of theadvisor may be provided in real-time or near real-time such that theuser may view or otherwise engage with the advisor live. In variousimplementations, multiple advisees and/or multiple advisors may interactlive via dashboard 310. In some implementations, an advisor (e.g.,“Advisor 2”) may be a robo-advisor helping one or more human advisors(e.g., “Advisor 1”) advise or otherwise assist one or more users (e.g.,Users 1 and 2).

FIG. 12 depicts an example graphical user interface 1200 of a potentialdashboard 310 according to example embodiments. During or after asession, the robo or human advisor may educate the user on the expensestrategy 1210 determined for that user to maintain or otherwise improveprogress towards a financial goal (e.g., improve a credit score). Asdepicted in the graphical user interface 1200 by the icon 1230, theconsumer computing device 120 may speak, or output the speech,conversation, voice, etc. of the human (or robo) advisor. For example,the advisor may suggest that the customer make micro-payments on eachcredit card by setting up auto-pay (weekly, bi-weekly, monthly, etc.)for each credit card to increase the amount of payments that the usermakes on time. In turn, the internal credit score of that user mayincrease more quickly. In some examples, an expense strategy 1210 may bedisplayed with a proposed change in spending, debt payoff,micropayments, etc. The expense strategy may be represented or furtherdetailed by one or more tabs 1220. The tabs 1220 may be structured todisplay the expense strategy details dynamically responsive to a userclicking or selecting a tab.

FIG. 13 depicts an example graphical user interface 1300 of a potentialdashboard 310 according to example embodiments. In some examples, theconsumer computing device 120 and/or the advisor computing device 130may output the graphical user interface 1300. The graphical userinterface 1300 may represent a digital dashboard with icons, images,data, charts, other graphics, etc., that may represent a financial goal,action plan, goal progress, etc. In some arrangements, the graphicaluser interface 1300 may include an image and/or video 1310representative of an advisor, or audio of the voice of an advisor(and/or a transcription of words spoken by the advisor). The image,video 1310, and/or the audio of the voice of the advisor may be providedin real-time or near real-time such that the user may view or otherwiseengage with the advisor live.

Illustrated in FIG. 14 is an example graphical user interface 1400 of anexample dashboard 310 according to example embodiments. In someexamples, the dashboard 310 is structured to present an expense strategynotification (e.g., a message, notice, account update, invitation,offer, etc.). In some implementations, the provider computing system 110may provide, send, or otherwise transmit an expense strategynotification to consumer computing device 120 associated with thecustomer. The expense strategy notification may be output or otherwisedisplayed via a user interface 200 (e.g., via a display, speaker, otheraudio/visual components of the consumer computing device 120). Theexpense strategy notification may indicate or otherwise inform the userof an action that affects the financial goal of the user as depicted inthe graphical user interface 1400. As shown in FIG. 14, the expensestrategy notification may output/indicate when the user took an actionthat affects the expense strategy. For example, the expense strategynotification may include a time stamp, date stamp (“May 3 Nancy paid . .. ,” “May 15 Nancy set spending limits,” etc.), or other indications ofwhen an action occurred. The expense strategy notification may include afinancial goal status based on the action or a plurality of actionstaken by the user that affect the expense strategy. In some examples,the provider computing device 110 may transmit an expense strategynotification to the consumer computing device 120 and/or advisorcomputing device 130 to inform the customer and/or advisor of the amountthat the customer can afford to spend or save based on the financialsituation of the customer. As shown, the expense strategy notificationmay include actions from a single user or a plurality of users (e.g.,“Bill saved $200 to New Car Goal”, “Nancy set up micro-payments,” etc.).Advantageously, users may find the expense strategy notification asmotivational and helpful to improve their financial status and to reachtheir financial goals (e.g., the goal to purchase a new car).

FIG. 15A depicts an example graphical user interface of an exampledashboard 310. The illustrated exchange may be between the customercomputing device 120 and the advisor computing device 130 (as part of ahuman advising session), and/or the exchange may be between the consumercomputing device 120 and the provider computing device 110 (as part of arobo-advising session). According to an example embodiment, the consumercomputing device 120 may present the expense strategy (e.g., advice,suggestions, etc.), which may have been, for example, generated by theprovider computing device 110 and/or updated via an advisor computingdevice 130, to the customer to help the customer review, maintain, orimprove progress towards a financial goal. The graphical user interfacemay be displayed such that the expense strategy may include iconsindicative of a goal status (e.g., checkmarks for completed oraccomplished, and exclamation points for incomplete or otherwiserequiring attention or response). In some implementations, iconspresented along a line may indicate an order or timeline for the goals(e.g., one goal may build on or otherwise follow another goal). Theicons may correspond to one or more strategies such as, but not limitedto, spending limits, micropayments, car pre-payments, car purchase, etc.In some examples, the icons may indicate whether the customer is offtrack or on track toward reaching the financial goal. For example, oneicon indicates that the customer is off-track with maintaining spendinglimits toward the goal of purchasing a new car. In some examples, thegraphical user interface may allow the user to drill down to receivemore detail. For example, a customer may click (or otherwise select)icon 1505 and/or provide a voice command to see more information abouthow the customer may get back on track toward meeting the financialgoal.

In some examples, if a customer selects one of the identified goals inFIG. 15A, another graphical user interface, such as the one depicted inFIG. 15B, may be presented. The graphical user interface may includeicons/graphics that represent, for example, the spending limits of acustomer. The graphical user interface may include an adjuster icon 1550(e.g., a graphical dial, slider control, etc.) structured to allow thecustomer (or advisor) to adjust/control, via dashboard 310, variousvalues (such as spending limits) as desired by the user. For example,the icon 1550 may be adjusted up, down, left, right, or in any otherdirection/position via the customer computing device 120 and/or advisorcomputing device 130. In some examples, the icon 1550 may represent aspending limit that is adjustable via the provider computing device 110(as part of robo-advising) or the advisor computing device 130 (as partof human advising). Responsive to the adjustment of the icon 1550, thespending limits of the user may then represent whether the user isoff-track or on-track toward reaching the financial goal. The providercomputing device 110, consumer computing device 120, and/or advisorcomputing device 130 may update profile 600 (e.g., by entering,updating, or revising values in fields corresponding to the goals andprogress 625 parameter). In some arrangements, the graphical userinterface may include an image and/or video representative of an advisor(e.g., at the top right in FIG. 15A) and/or audio of the voice of anadvisor in real-time or near real-time such that the user may view orotherwise engage with the advisor live. The graphical user interface mayinclude a selection (e.g., the virtual “Save Changes” button) to allowthe customer or advisor to save adjustments to the expense strategy,spending limits, etc.

FIG. 15C depicts an example graphical user interface of an potentialdashboard 310 according to example embodiments. In variousimplementations, the provider computing device 110 may present thegraphical user interface depicted in FIG. 15C to the customer via theconsumer computing device 120 and/or to the advisor via advisorcomputing device 130. In some examples, the graphical user interface maybe presented to the user in response to the user clicking an icon orbutton and/or providing a voice command as described herein. Thegraphical user interface may include a notification, message, and/orupdate that includes the current status of the user toward meeting afinancial goal. As depicted in FIG. 15C, the checkmark icon (formerly anexclamation point) adjacent to “Spending Limits” may indicate thecustomer is back on track based on, for example, the limits,transactions, adjustments made (via, e.g., the graphical user interfaceof FIG. 15B), or other actions of the customer.

FIG. 16 depicts an example graphical user interface of an potentialdashboard 310. According to an example embodiment, the providercomputing device 110 may present the graphical user interface to thecustomer and/or advisor via the consumer computing device 120 and/or theadvisor computing device 130. In some examples, the graphical userinterface may represent a digital dashboard that includes icons, images,data, charts (e.g., the graphical charts/graphs), other graphics, etc.,that may represent the credit score, spending trends, status of thecustomer toward reaching the financial goal, etc. According to thecurrent example depicted in FIG. 16, the customer has made 100% progresstoward the financial goal of buying a new car. The content of thedigital dashboard may be provided in real-time or near real-time by theprovider computing device 110. Advantageously, the customer may beinformed of the current status of reaching the financial goal based onthe real-time or near real-time update of the digital dashboard.

FIG. 17 is an example graphical user interface of a potential dashboard310 according to an example embodiment. In some examples, the providercomputing device 110 is structured to generate an expense strategynotification (e.g., a message, SMS, notice, account update, invitation,offer, etc.). The provider computing device 110 may provide, send, orotherwise transmit the expense strategy notification to a consumercomputing device 120 and/or advisor computing device 130. The expensestrategy notification may be output or otherwise presented via adisplay, speaker, other audio/visual components of the consumercomputing device 120 and/or the advisor computing device 130. Forexample, the expense strategy notification may include an offer for anauto loan transmitted to the consumer computing device 120 of thecustomer when the customer meets the financial goal as identified by theprovider computing device 110 and/or advisor computing device 130. Insome implementations, an expense strategy notification that includes anoffer may be transmitted to the consumer computing device 120 inresponse to the consumer computing device 120 transmitting an expensestrategy notification (e.g., a SMS that includes information that thecustomer is ready to buy the car, a home, etc.) to the providercomputing device 110 and/or the advisor computing device 130.

The embodiments described herein have been described with reference todrawings. The drawings illustrate certain details of specificembodiments that implement the systems, methods and programs describedherein. However, describing the embodiments with drawings should not beconstrued as imposing on the disclosure any limitations that may bepresent in the drawings.

It should be understood that no claim element herein is to be construedunder the provisions of 35 U.S.C. § 112(f), unless the element isexpressly recited using the phrase “means for.”

The various components of the computing systems and user devices (suchas modules, monitors, engines, trackers, locators, circuitry,interfaces, sensors, etc.) may be implemented using any combination ofhardware and software structured to execute the functions describedherein. In some embodiments, each respective component may includemachine-readable media for configuring the hardware to execute thefunctions described herein. The component may be embodied at least inpart as one or more circuitry components including, but not limited to,processing circuitry, network interfaces, peripheral devices, inputdevices, output devices, sensors, etc. In some embodiments, a componentmay take the form of one or more analog circuits, electronic circuits(e.g., integrated circuits (IC), discrete circuits, system on a chip(SOCs) circuits, etc.), telecommunication circuits, hybrid circuits, andany other type of circuit. In this regard, the component may include anytype of element for accomplishing or facilitating achievement of theoperations described herein. For example, a compoenent as describedherein may include one or more transistors, logic gates (e.g., NAND,AND, NOR, OR, XOR, NOT, XNOR, etc.), resistors, multiplexers, registers,capacitors, inductors, diodes, wiring, and so on).

The component may also include one or more processors communicativelycoupled to one or more memory or memory devices. In this regard, the oneor more processors may execute instructions stored in the memory or mayexecute instructions otherwise accessible to the one or more processors.In some embodiments, the one or more processors may be embodied invarious ways. The one or more processors may be constructed in a mannersufficient to perform at least the operations described herein. In someembodiments, the one or more processors may be shared by multiplecircuits (e.g., circuit A and circuit B may comprise or otherwise sharethe same processor which, in some example embodiments, may executeinstructions stored, or otherwise accessed, via different areas ofmemory). Alternatively or additionally, the one or more processors maybe structured to perform or otherwise execute certain operationsindependent of one or more co-processors. In other example embodiments,two or more processors may be coupled via a bus to enable independent,parallel, pipelined, or multi-threaded instruction execution. Eachprocessor may be implemented as one or more general-purpose processors,application specific integrated circuits (ASICs), field programmablegate arrays (FPGAs), digital signal processors (DSPs), or other suitableelectronic data processing components structured to execute instructionsprovided by memory. The one or more processors may take the form of asingle core processor, multi-core processor (e.g., a dual coreprocessor, triple core processor, quad core processor, etc.),microprocessor, etc. In some embodiments, the one or more processors maybe external to the apparatus, for example the one or more processors maybe a remote processor (e.g., a cloud based processor). Alternatively oradditionally, the one or more processors may be internal and/or local tothe apparatus. In this regard, a given components or parts thereof maybe disposed locally (e.g., as part of a local server, a local computingsystem, etc.) or remotely (e.g., as part of a remote server such as acloud based server). To that end, a component as described herein mayinclude elements that are distributed across one or more locations.

An example system for implementing the overall system or portions of theembodiments might include a general purpose computing computers in theform of computers, including a processing unit, a system memory, and asystem bus that couples various system components including the systemmemory to the processing unit. Each memory device may includenon-transient volatile storage media, non-volatile storage media,non-transitory storage media (e.g., one or more volatile and/ornon-volatile memories), etc. In some embodiments, the non-volatile mediamay take the form of ROM, flash memory (e.g., flash memory such as NAND,3D NAND, NOR, 3D NOR, etc.), EEPROM, MRAM, magnetic storage, hard discs,optical discs, etc. In other embodiments, the volatile storage media maytake the form of RAM, TRAM, ZRAM, etc. Combinations of the above arealso included within the scope of machine-readable media. In thisregard, machine-executable instructions comprise, for example,instructions and data which cause a general purpose computer, specialpurpose computer, or special purpose processing machines to perform acertain function or group of functions. Each respective memory devicemay be operable to maintain or otherwise store information relating tothe operations performed by one or more associated circuits, includingprocessor instructions and related data (e.g., database components,object code components, script components, etc.), in accordance with theexample embodiments described herein.

Any foregoing references to currency or funds are intended to includefiat currencies, non-fiat currencies (e.g., precious metals), andmath-based currencies (often referred to as cryptocurrencies). Examplesof math-based currencies include Bitcoin, Litecoin, Dogecoin, and thelike.

It should be noted that although the diagrams herein may show a specificorder and composition of method steps, it is understood that the orderof these steps may differ from what is depicted. For example, two ormore steps may be performed concurrently or with partial concurrence.Also, some method steps that are performed as discrete steps may becombined, steps being performed as a combined step may be separated intodiscrete steps, the sequence of certain processes may be reversed orotherwise varied, and the nature or number of discrete processes may bealtered or varied. The order or sequence of any element or apparatus maybe varied or substituted according to alternative embodiments.Accordingly, all such modifications are intended to be included withinthe scope of the present disclosure as defined in the appended claims.Such variations will depend on the machine-readable media and hardwaresystems chosen and on designer choice. It is understood that all suchvariations are within the scope of the disclosure. Likewise, softwareand web implementations of the present disclosure could be accomplishedwith standard programming techniques with rule based logic and otherlogic to accomplish the various database searching steps, correlationsteps, comparison steps and decision steps.

The foregoing description of embodiments has been presented for purposesof illustration and description. It is not intended to be exhaustive orto limit the disclosure to the precise form disclosed, and modificationsand variations are possible in light of the above teachings or may beacquired from this disclosure. The embodiments were chosen and describedin order to explain the principals of the disclosure and its practicalapplication to enable one skilled in the art to utilize the variousembodiments and with various modifications as are suited to theparticular use contemplated. Other substitutions, modifications, changesand omissions may be made in the design, operating conditions andarrangement of the embodiments without departing from the scope of thepresent disclosure as expressed in the appended claims.

What is claimed is:
 1. A service provider computing system comprising: adatabase with a user profile corresponding to a user; and a networkinterface configured to communicatively couple the service providercomputing system to: a first computing device having a sound sensor fordetecting ambient sounds and a first set of one or more user interfacesfor perceptibly presenting information to the user and receiving userinputs; and a second computing device having a second set of one or moreuser interfaces for perceptibly presenting information to an advisor andreceiving advisor inputs; wherein at least one of the first computingdevice and the service provider computing system is configured to:detect a goal by: capturing ambient sounds using the sound sensor of thefirst computing device; extracting a set of one or more voice inputs ofthe user from a subset of the ambient sounds captured using the soundsensor; and identifying the goal based at least on an analysis of theset of voice inputs; initiate a live communication session between thefirst and second computing devices; and present a virtual dashboard viathe first and second sets of user interfaces during the livecommunication session, the virtual dashboard being configured toperceptibly present, via the second set of user interfaces, anidentification of the goal; wherein at least one of the first computingdevice and the service provider computing system is further configuredto initiate a first robo-advising session before initiating the livecommunication session; and wherein the virtual dashboard is furtherconfigured to present an activatable link which, when activated via thefirst or second set of user interfaces, terminates the livecommunication session and initiates a second robo-advising session. 2.The system of claim 1, wherein at least one of the first computingdevice and the service provider computing system is further configuredto identify select data from the user profile relevant to the goal, andwherein the virtual dashboard is further configured to perceptiblypresent the select data.
 3. The system of claim 1, wherein the soundsensor of the first computing device is configured to pervasivelycapture ambient sounds to detect goals.
 4. The system of claim 1,wherein at least one of the first computing device and the serviceprovider computing system is further configured to detect an urgency ofthe goal based on at least one of speed, tone, or aggression of userspeech.
 5. The system of claim 1, wherein the virtual dashboard isfurther configured to perceptibly present a graphic depiction of theuser's progress towards achieving the goal.
 6. The method of claim 1,wherein the virtual dashboard is further configured to present at leastone of an advisor image, an advisor video, and an advisor audio.
 7. Thesystem of claim 1, wherein the virtual dashboard is further configuredto present, via the first set of user interfaces, inputs received viathe second set of user interfaces following presentation of theidentification of the goal.
 8. The system of claim 1, wherein the set ofvoice inputs is identified based at least in part on a biometric voicesignature of the user.
 9. The system of claim 8, wherein the ambientsounds include voice inputs of a second user, and wherein the voiceinputs of the second user are excluded from the set of voice inputsbased on a mismatch with the biometric voice signature of the user. 10.The system of claim 1, wherein the virtual dashboard is furtherconfigured to present, via the second set of user interfaces,information exchanged during a prior live communication session.
 11. Thesystem of claim 1, wherein the sound sensor is a first sound sensor,wherein the second computing device further comprises a second soundsensor, and wherein at least one of the first computing device, thesecond computing device, and the service provider computing device isconfigured to detect the goal based on a combination of multiplefragmented issue indicators identified in multiple voice inputs capturedusing the first and second sound sensors of the first and secondcomputing devices.
 12. The system of claim 1, wherein the set of voiceinputs is a first set of voice inputs and the user is a first user,wherein at least one of the first computing device and the serviceprovider computing system is further configured to: extract a second setof one or more voice inputs of a second user from the subset of theambient sounds captured using the sound sensor; and identify the goalbased at least on an analysis of both the first and second sets of voiceinputs.
 13. The system of claim 12, wherein the first and second sets ofvoice inputs are separated by multiple days.
 14. A service providercomputing system comprising: a database with a user profilecorresponding to a user; and a network interface configured tocommunicatively couple the service provider computing system to: a firstcomputing device having a sound sensor for detecting ambient sounds anda first set of one or more user interfaces for perceptibly presentinginformation to the user and receiving user inputs; and a secondcomputing device having a second set of one or more user interfaces forperceptibly presenting information to an advisor and receiving advisorinputs; wherein at least one of the first computing device and theservice provider computing system is configured to: detect a goal by:capturing ambient sounds using the sound sensor of the first computingdevice; extracting a set of one or more voice inputs of the user from asubset of the ambient sounds captured using the sound sensor; andidentifying the goal based at least on an analysis of the set of voiceinputs; initiate a live communication session between the first andsecond computing devices; and present a virtual dashboard via the firstand second sets of user interfaces during the live communicationsession, the virtual dashboard being configured to perceptibly present,via the second set of user interfaces, an identification of the goal;wherein at least one of the first computing device and the serviceprovider computing system is further configured to: detect arobo-advising transition trigger during the live communication session;terminate the live communication session; and initiate a robo-advisingsession.
 15. The system of claim 14, wherein the live communicationsession is a first live communication session, and wherein at least oneof the first computing device and the service provider computing systemis further configured to: detect, during the robo-advising session, ahuman-advising transition trigger; initiate a second live communicationsession between the first and second computing devices in response todetection of the human-advising transition trigger; and provide thevirtual dashboard to the first and second computing devices during thesecond live communication session, the virtual dashboard beingconfigured to perceptibly present information exchanged between thefirst and second devices during the first live communication session andduring the robo-advising session.
 16. The system of claim 15, wherein atleast one of the first computing device and the service providercomputing system is further configured to present, via the second set ofuser interfaces, information from the first live communication sessionand the robo-advising session.
 17. A computing device comprising: asound sensor for detecting ambient sounds; a first set of one or moreuser interfaces for perceptibly presenting information to a user andreceiving user inputs; a network interface configured to communicativelycouple the computing device to a second computing device having a secondset of one or more user interfaces for perceptibly presentinginformation to an advisor and receiving advisor inputs; and a processorand memory having instructions that, when executed by the processor,cause the processor to: pervasively detect ambient sounds using thesound sensor; extract a set of one or more voice inputs of the user froma subset of the ambient sounds; identify a goal of the user based atleast on an analysis of the set of voice inputs; initiate a livecommunication session with the second computing device; and present avirtual dashboard via the first set of user interfaces during the livesession, the virtual dashboard being configured to perceptibly present,via the second set of user interfaces, an identification of the goal;wherein the memory further comprises instructions that, when executed bythe processor, cause the processor to: initiate a robo-advising sessionbefore initiating the live communication session with the secondcomputing device; and perceptibly present information from therobo-advising session in the virtual dashboard during the livecommunication session.
 18. The computing device of claim 17, wherein thememory further comprises instructions that, when executed by theprocessor, cause the processor to: detect a robo-advising transitiontrigger during the live communication session; and terminate the livesession in response to detection of the robo-advising transitiontrigger.
 19. The device of claim 17, wherein the network interface isfurther configured to communicatively couple the computing device to aservice provider computing system storing, in a database, a user profilecorresponding with the user, and wherein the virtual dashboard isfurther configured to: present, via the second set of user interfaces,select data from the user profile determined, by at least one of thecomputing device, the second computing device, and the service providercomputing system, to be relevant to the goal; and present, via the firstset of user interfaces, inputs received via the second set of userinterfaces following presentation of the select data.
 20. The device ofclaim 17, wherein the virtual dashboard is further configured to presenta graphic depiction of the user's progress towards achieving the goal.21. A method comprising: pervasively detecting ambient sounds using asound sensor of a first computing device; extracting a set of one ormore voice inputs of a user from a subset of the ambient sounds;identifying a goal of the user based at least on an analysis of the setof voice inputs; initiating a live communication session between thefirst computing device and a second computing device; and providing avirtual dashboard configured to perceptibly present to the secondcomputing device an identification of the goal; wherein the methodfurther comprises initiating a robo-advising session before initiatingthe live communication session, and perceptibly presenting informationfrom the robo-advising session in the virtual dashboard during the livecommunication session.
 22. The method of claim 21, wherein the virtualdashboard is further configured to present a graphical depiction of theuser's progress towards achieving the identified goal.
 23. A methodcomprising: pervasively detecting ambient sounds using a sound sensor ofa first computing device; extracting a set of one or more voice inputsof a user from a subset of the ambient sounds; identifying a goal of theuser based at least on an analysis of the set of voice inputs;initiating a live communication session between the first computingdevice and a second computing device; providing a virtual dashboardconfigured to perceptibly present to the second computing device anidentification of the goal; detecting a robo-advising transition triggerduring the live communication session; and terminating the live sessionin response to detection of the robo-advising transition trigger. 24.The method of claim 23, wherein the live communication session is afirst live communication session, and wherein the method furthercomprises: initiating a robo-advising session following termination ofthe live session; detecting, during the robo-advising session, ahuman-advising transition trigger; initiating a second livecommunication session between the first computing device and the secondcomputing device in response to detection of the human-advisingtransition trigger; and perceptibly presenting, in the virtualdashboard, information exchanged between the first and second devicesduring the first live communication session and during the robo-advisingsession.
 25. The method of claim 23, wherein detecting the robo-advisingtransition trigger during the live session comprises receiving, via oneof the user interfaces of the first and second computing devices, asignal indicating activation of a visually-perceptible link forindicating a desire to return to robo-advising.